Research Computing Teams #132, 30 Jul 2022
Hi!
Last week we talked about ways to say no to incoming requests; besides a flat-out no, I mentioned the possibility of involving another team, or supporting the research group in doing the work themselves. RCT community member Adam DeConinck sent in another suggestion:
Occasionally, I’ve seen requests come in for work that the research computing team isn’t going to do; but which is also not something that another provider exists to do, and which the customer can’t do themselves even with training. When that happens, the “support” I’ve been able to offer is to join the customer in advocating for change. For example, aggregate similar requests and find commonalities; then organize the customers involved and advocate to upper management that they provide resources for this work to be done. That’s often not terribly satisfying, and I’ll admit that my success rate in doing this isn’t very high. (Non-zero, though!) But it’s often the only way I’ve found to create new classes of service within an existing organization.
This is a great suggestion, taking the long term view - and by lending your voice to the research groups’ in advocating for support for different kinds of work, it turns the situation into “your team and the research group vs the problem” rather than “your team disagreeing with the research group”.
This is the time of year when I’m just beginning to see the “out of office” emails in response to the newsletter - I expect them to grow more numerous in the coming month. Probably because of that, one question I got asked recently (and went up on the topics poll, receiving an upvote) was how to handle going on vacation.
Preparing to go on vacation is a great opportunity to practice delegation — to give your team members opportunities to grow in responsibility. That growth in responsibility can be temporary, but it can also be the beginning of a permanent handoff of some activities or responsibilities. One link I sent out back in #79, Always Be Quitting, described this mindset quite well and has been commented on several times by community members:
The key lies in NOT being indispensable. […] Paradoxically, by being disposable, you free yourself. You make it easier for yourself to grow into a higher-level role and you make it easier for yourself to change the projects you work on.
By bringing others into meetings you take, by documenting your knowledge and the state of projects, you make it easier for yourself to step back from some responsibilities to make room for other work, while enabling others to take them on. Vacation is a fantastic opportunity to trial-run delegation, to give you and a team member the opportunity to test the delegation in a very time-boxed way that’s readily explainable to others.
One-on-ones are are a great vehicle for finding out what professional growth team members are interested in - the RCT one-on-one template cover sheet has a spot for “what’s next” to keep track of possible next steps on their growth, and the quarterly goal setting and review forms include regular check-ins on career goals and a opportunity to start making explicit plans. Key to doing this well is the idea of a responsibility ladder (#12), or of task-relevant maturity (#50). Giving people growth opportunities while setting them up to succeed means not just dropping them in the deep end, but by giving them responsibility for gradually increasing scope in that area. This article on an engineering team where everyone is a leader, also from #12, describes the process in the context of software development projects in particular, but applies more widely.
When we have a good sense of who are willing and might be soon be ready to take on particular aspects of our current work, those are now target areas in which to tidy up our own work. We can make sure our documentation of the state of the effort is current, or start writing up the processes we go through, or collect meeting notes. Those can then be shared, and we can start bringing the team members to relevant meetings. We can review the state of those activities in one-on-ones, in preparation for any handoff. They could practice taking a meeting for us in that area, updating the one notes, and debriefing afterwards if some conflict arises (or can be arranged to arise).
If this has already been done before going off on vacation, great! People should be prepared and confident to step in for you on those activities over the coming weeks. But if not, in areas where there’s unlikely to be huge fires to be put out or decisions to be made in the short term, don’t let that stop you from handing off tasks in your absence. Do them and you the favour of being explicit about what they should and shouldn’t feel empowered to do on their own in that area, and what should wait for your return - but try to make that last as little as possible.
This article from #85, managers need vacations too, gives a nice overall checklist when getting ready to be away:
- Prep a “While I’m Away” list - a list of things that you expect may come up, or deadlines, or special notes or reminder
- Put one person in charge - to keep things moving, and to handle any things that weren’t in explicitly delegated areas: again, let them know what is and isn’t in scope
- Ask your team to keep a collaborative set of notes - this was a great idea I hadn’t seen before this article - everyone keeps notes on what happened in your absence in one document. This lets them share information internally, and gives you one briefing document to catch up on
- Turn on your Out of Office Alert - directing correspondants to the relevant people
- Do not reply to your email or voicemails
- Carve out 2 hours in the morning when you get back to get caught up
You don’t necessarily have to start doing all of this all at once your next vacation (or conference trip, or…), but these steps, combined with some preparation for delegating particular responsibilities, are a great place to aim to be after the next few absences. Debriefing afterwards will give both you and your team members an opportunity to discuss whether you’d both be comfortable taking on the responsibility permanently, with you still there to coach and advise,
Does that seem helpful? What other approaches have you taken to handing off responsibilities while you’re away? Let me know - just hit reply or email me at jonathan@researchcomputingteams.org.
Speaking of vacation, I’m going to take the next two weeks off from the newsletter - I’ll be back on Aug 19th or 20th (I’m going to try to get back onto a Friday schedule, although we’ll see how that goes).
With that, on to the roundup!
Managing Teams
Give Away Your Legos Matrix - Evan Rutledge Borden
Very relevant to the discussion above - even after you get back from vacation, what tasks should you not take back on? Borden writes this article inspired by Give Away Your Legos by Molly Graham. (Graham’s article article was also recently recommended by RCT community member Rodrigo Ortega Polo, after the Bioinfo-core session he co-organized). The article is almost entirely the diagram below.
There’s only two things I’d add. The first is that over time, the bar for things you keep doing because you enjoy them should get raised higher and higher. It’s not bad, necessarily, to still hoard a couple of activities to yourself that you love. Yes, these are activities your team members will likely need to grow into eventually (such as when you’re away!). But maybe they’re the tasks that give you sine needed energy and engagement. The key is not to do it unthinkingly, but to realize what you’re doing and why.
The second is something RCT community member Scott Delinger has reminded me of a couple of times. Any even cursory audit of tasks such as this one should include a filter for “does anyone really need to keep doing this?” Love it or not, complex or not, if the team just dropped this task entirely how bad would it be, really? If no one did it while you were away, and you just didn’t start doing it again, is that something you could get away with? Do the benefits really outweigh the costs of your most precious resource, time? Usually the answer will be that you have to keep doing it, but when you do find stuff to stop doing that’s found extra time.
Note that in the diagram below, “automate” could literally mean just have a computer do the work, but it can also be work simplification by folding some task into some other regularly occurring process.
How to Deliver Bad News - Ed Batista
Whether it’s discussions with stakeholders, institutional decision makers, job candidates, or team members, we often have to be the bearer of bad news. It doesn’t get easy, exactly, but when we’re new to it we often make it even harder on ourselves than it has to be. That’s the part we can do something about.
Batista writes specifically about delivering bad news to more senior decision makers or stakeholders. Our part of these conversations is pretty simple (not easy, but simple) - he has a three-part formula:
- Here’s What Happened
- Here’s Why (or Here’s What I’ve Learned So Far)
- Here’s What I’m Planning to Do [LJD: and being open to suggestions or directions]
We have to deliver bad news in a timely manner, but we should at least be prepared to talk about what we know about why something happened and have an initial recommendation for next steps.
Batista then describes three things that make things go a little easier - all of which are things we can influence:
- Trust - the more one-on-one discussions we’ve had with the people we’re talking to, and the more trust we’ve earned over time, the more smoothly these conversations go
- [our own] Emotional regulation - staying calm, and not getting defensive when the obvious and necessary alarm registers and questions get raised
- [our own] Perspective - this situation may feel like the end of the world in the moment, but it isn’t.
Reviving an R&D pipeline: a step change in the Phase II success rate - Wu et al, Drug Discovery Today (2021) 26:308
I’ve talked before about the importance of specialization for being effective as a team, while not siloing (#114) - of focussing our efforts on particular kinds of problems someone external would recognize, while not necessarily limiting ourselves to particular set of technologies or approaches or tools that we use internally on those problems.
This isn’t an approach that we’re forced into because we only have small teams; it’s a more general approach than that. Here a group at Pfizer, a 79,000 employee pharmaceutical behemoth, describes how they improved their Phase II success rate from 19% to 53% (2.8x!). They did this sharpening their focus onto a smaller number of therapeutic areas, so they understood the problem domain better, while simultaneously increasing the number of approaches and technologies they brought to bear on that smaller number of problems.
In HBR there’s an article by Liz Fosslein on How to Pace Yourself at Work While Pregnant. It’s also useful for suggestions those of us like me who don’t know first or even second hand the challenges of pregnancy how to support our coworkers and team members who are pregnant.
Technical Leadership
How to Resolve These Five Problems of Struggling Software Engineers - George Marklow
Sometimes new and junior team members have individualized needs that some coaching and resources can help with. Other times, if new team members keep having similar problems, there may be knowledge-sharing or infrastructure problems in the team that can be resolved. Marklow covers both sets here:
- Slow progress of work - maybe there’s not enough internal documentation, which they could write a first draft of as they are shown the ropes; or maybe they just need some particular knowledge, in which case seniors and leads could share and document helpful resources. Or maybe confidence is a problem, in which case getting them to present work of increasing scope could help.
- Understanding the tickets/user stories - the key is to get this understanding as quickly as possible, having the team member coordinate with those that wrote the ticket, and propose approaches like have them write some of the documentation first to make sure they’re solving the right problem
- Lack of core understanding (problem/database/workflow) - as with learning needs, this is likely a documentation or helpful resource sharing problem, which can be fixed here with a walkthrough and a writeup, and will hopefully help new team members
- Pull request/collaboration issues - being more explicit about expectations, having checklists, and reviewing previous PRs can all help here
- Anxiety (“stage fright”) about pushing into production - again, documentation, expectations, and checklists help here.
Science Policy, Funding, and Research Computing & Data
A sobering reminder that our research community colleagues don’t receive equitable treatment Decades of systemic racial disparities in funding rates at the National Science Foundation by Chen et al. The results are even worse than the headline granting rate numbers suggest - many Black colleagues’ NSF research grants, for instance, aren’t for research but for education or outreach.
Mapping the future of Research Management - European Association of Research Managers and Administrators (EARMA)
Research management roadmap project ‘ready to launch’ - Craig Nicholson, Research Professional News
It’s nice to see that slowly, there’s growing recognition of the need for a professional cadre of research staff. It’s happening particularly slowly in the people or project/product management areas, but it is happening:
Europe’s leading organisations that represent research managers have welcomed the award of €1.5m from the Horizon Europe programme, to fund an unprecedented co-creation process that aims to define the future of the profession. […] The role of research management has undergone dramatic changes, in response to the ever-changing demands of the social and political context of public-funded research. Research managers are now an integral and vital part of the research ecosystem, and take many forms, including policy advisers, project managers, financial support, data stewards, business developers and knowledge brokers.
Research Software Development
On the accuracy and performance of the lattice Boltzmann method with 64-bit, 32-bit and novel 16-bit number formats - Lehmann et al
It’s been clear for a long time that memory bandwidth is more of a limitation than raw compute for most scientific codes, but I think for a long time people have been hoping that some kind of hardware advances would make that pendulum swing back. Unfortunately, it doesn’t look likely. So the options are improving latency hiding one way or another and/or reducing memory bandwidth requirements by using smaller data types.
We’re starting to see some of the lower-precision floating point codes now. Here’s a nice example of lattice Boltzmann in particular doing very well at lower precisions, with some care put into the algorithm to not unduly require range and precision by, for instance, normalizing density functions. The authors here distinguish between the storage precision and the precision in which the results are calculated - e.g. FP64/FP32 means that the data is stored in memory in FP32 at each time step, but intermediate calculations are done in FP64.
Here the results from FP32 and FP64 are indistinguishable, and with the “right” FP16 precision, noise is well controlled. Here among other formats they play with posits, a non-IEE754 approach, for storage; there’s no hardware support for these, but the savings in memory bandwidth almost balance out the need for software conversion to FP32.
ML-Enhanced Code Completion Improves Developer Productivity - Maxim Tabachnyk and Stoyan Nikolov
It turns out that Google has had its own internal copilot like ML programming assistant for a while now, for eight programming languages, and they find that it provides modest but measurable improvements in productivity:
We compare the hybrid semantic ML code completion of 10k+ Googlers (over three months across eight programming languages) to a control group and see a 6% reduction in coding iteration time (time between builds and tests) and a 7% reduction in context switches (i.e., leaving the IDE) when exposed to single-line ML completion. These results demonstrate that the combination of ML and SEs can improve developer productivity. Currently, 3% of new code (measured in characters) is now generated from accepting ML completion suggestions.
Google of course has the huge advantage that it has a huge code base, with a vast history of of code reviews, famously sitting in a single monorepo, to train their models on. But it’s interesting to see that even with this technology in its infancy, there are noticeable benefits. 3%, 6%, or 7% may seem like small numbers, but 6% of a working year is about three work weeks.
Research Data Management and Analysis
It’s great to see data science core facilities pushing for a growing role for research data management, especially in the service of open science. Here John Borghi and Ana Van Gulick write about Promoting Open Science Through Research Data Management in the Harvard Data Science Review.
Whether you lean towards R or Python, RStudio has been inarguably a force for good in the data science community along several dimensions. So the announcement of RStudio, Inc’s name change to Posit, reflecting a change of focus to include Python (including a python version of Shiny!) is pretty exciting. Jupyter is great and all, but RStudio’s very clear offramp of code from interactive exploration and notebooks into version control and unit tests is extremely helpful, and the python data science community doesn’t have anything like it. I can’t wait to see what the new company dos.
Research Computing Systems
Metrics of financial effectiveness: Return On Investment in XSEDE, a national cyberinfrastructure coordination and support organization - Stewart et al, Proceedings of PEARC ’22
There were a lot of great papers in the proceedings of PEARC’22, and I’ll highlight a few of them in the coming months that I think are particularly relevant for our community.
In this first instalment, the authors take a look at the last six years of XSEDE, and try to answer the simple question “is it worth it for funders to continue funding such efforts”? They focus here on activities and outputs - for the services delivered, internally within the inter-institutional collaboration, and externally to researchers, how much would it have cost to do the same work absent the support of XSEDE?
This requires some thought about what exactly those services are, who would have done them in the counterfactual case, and how much effort it would have taken. The authors describe how they went through this process. For the last they relied on surveys of researchers, and estimates from consortia.
The discussion and the results are interesting, and very believable. (A huge problem in this field is wildly unsupportable numbers - for instance a famous factoid that circulated for a while claiming that the ROI for HPC investment in industry was 50x). For a couple of examples, having a common pool of expertise saved (for instance) local system administrators figuring out how to do the work themselves, and the extended consulting services saved countless hours of research group time. (A favourite nugget - when asking a researcher how much work the extended support services saved their group, if the response was that the work simply wouldn’t have been possible at all without the support, an apparently pretty common response, the authors simply capped off the total amount of efforts saved as 2 people years). The estimated value of the total amount of time saved was 1.5x the amount that XSEDE actually cost. From the authors discussions I felt that this was ab admirably conservative figure.
Like most good papers, the answers provided by the paper suggest new questions:
- The ROI over the course of the six years considered was fairly flat (excepting some boundary effects at the start and end of the period of study). Does that reflect the fact that the Teragrid/XSEDE community is quite mature and has gotten things down to a science? Or does it suggest that there’s untapped room for growth that’s not happening?
- How would we find out if some of those services - or some of the audiences for the services - had greater impact and ROI than others? If so, should efforts be focussed there?
- How would we determine if there’s a “more than the sum of their parts” value to the collection of services collectively?
- The benefits internal services offered were largely about time savings from other people not having to do the same tasks - how would one investigate/compare to see if other activities could have provided the same outcomes and impacts for still less cost?
But even this paper by itself is extremely useful. It’s great to see the community bringing in real business and accounting expertise to produce these kinds of reports to advocate for their services and their researcher community to funders.
IBM Uses Power10 CPU as an I/O Switch - Timothy Prickett Morgan, The Next Platform
Sharp-eyed Morgan notices an intriguing detail in some architecture diagrams out of big blue. An entire Power 10 chip (within a 2-chip package), a not-inexpensive piece of silicon, appears to have all its cores turned off and instead is used to focus entirely on I/O switching in the Power S1022 and S1024 systems.
We’re well into the era where raw compute power matters little in and of itself; rather, balanced throughput across an entire integrated system is what’s crucial. This is why I’m low-key furious that we’re still ranking systems by HPL benchmarks as if how fast a computing cluster can run its “hello, world” burn-in test matters.
Random
Still arguing about tabs vs spaces? 2-spaces per indent vs 4? Pffft. You are like baby. No, I present to you - Fibonacci indenting.
Testing a tool against 14 different database products using Github Actions.
I actually have to do this now, but hadn’t come up with a principled approach to it - juggling multiple committer email addresses with git.
I mentioned the C23 #embed last time - here’s what people have to do to portably include binary blogs in an executable in a world without #embed.
C++20 implemented Python f-string like string interpolation with string::format.
The humble yes command and how a naive implementation can be 10-1000x slower than a fully optimized version, in case you need to output ‘y’ at 3GB/s.
This pure python game of life streams gzip-compressed MPEG video to stdout at 60 1080p frames per second, using bigints for efficiency (!!!).
I like to think I’m pretty open-minded about technology choices, but… the case for C# and .net (as compared to server-side javascript, though, so the bar’s set pretty low).
A NASA video of computational fluid dynamics highlights from 1989.
Facebook Meta hates the leap second.
More than you wanted to know about the tar archive format, and why it extracts in quadratic time.
Maybe more than you wanted to know about the Solaris linkers, loader, and libraries, but ends up being a pretty good walk through of what linkers do, and the ELF ABI.
DuckDB now persists ART indices - here’s how they work.
And here’s how SQLite file I/O works. Fly.io used that filesystem level understanding to develop fuse-based filesystem specifically for replicating SQLite databases across a cluster.
A nascent community (and software tools) for binary translation from x86 to Arm, specifically to deal with the difference in memory models under concurrency.
Nala, a tui-based front-end to apt.
Your python or go command-line tools increasingly have spiffy TUI interfaces - now so can your shell scripts, with charm gum.
That’s it…
And that’s it for another week. Let me know what you thought, or if you have anything you’d like to share about the newsletter or management. Just email me or reply to this newsletter if you get it in your inbox.
Have a great weekend, and good luck in the coming week with your research computing team,
Jonathan
About This Newsletter
Research computing - the intertwined streams of software development, systems, data management and analysis - is much more than technology. It’s teams, it’s communities, it’s product management - it’s people. It’s also one of the most important ways we can be supporting science, scholarship, and R&D today.
So research computing teams are too important to research to be managed poorly. But no one teaches us how to be effective managers and leaders in academia. We have an advantage, though - working in research collaborations have taught us the advanced management skills, but not the basics.
This newsletter focusses on providing new and experienced research computing and data managers the tools they need to be good managers without the stress, and to help their teams achieve great results and grow their careers.
Jobs Leading Research Computing Teams
This week’s new-listing highlights are below; the full listing of 218 jobs is, as ever, available on the job board.
Principal Lead Software Engineer, eScience Institute - University of Washington, Seattle WA USA
The eScience Institute is seeking outstanding candidates for the position of Principal Lead Software Engineer (multiple openings). We are building a diverse team of software engineers who will bring their unique backgrounds and expertise to the UW community. These software engineers will work on impactful research projects, infusing them with the software industry’s best practices, and delivering reusable, open source software that will accelerate future research in areas like climate change, health, energy and basic science. We are looking for qualified software engineers with dual backgrounds in science and technology, who will be central to the SSEC mission to support data driven research by enabling the development of new software tools and user communities serving greater scientific goals.
Senior Principal Research Scientist, Data Privacy - CSIRO, Sydney AU
In your role as Senior Principal Researcher in CSIRO, you will lead and conduct innovative research producing scientific achievements aligned with CSIRO’s strategies. You may be engaged in scientific activity ranging from fundamental research to investigating the specific industry or community problems. You will have the opportunity to lead and conduct impactful research, build and maintain networks, mentor and work in collaboration with other researchers, and drive initiatives to secure project funds. You will contribute to the strategic research directions of the group, initiate and pursue new ideas and approaches that create new concepts, and provide scientific leadership to your team and group.
Research Engineering Team Lead, Applied - DeepMind, New York City NY USA
The Applied team collaborates closely with a wide variety of teams across Google/Alphabet, leveraging DeepMind expertise to deploy advanced machine learning algorithms with the goal of improving Alphabet products and services. We are a driven, collaborative, diverse team based in London and Mountain View. Our current and past engagements include teams in Cloud, Android, Assistant, Youtube and Maps. We collaborate closely with DeepMind’s and Google’s Research teams on several projects. Each project typically consists of a team of engineers working closely with our product partners and with our researchers, product managers and program managers.
Group Leader, Quantum Computing and Sensing - Oak Ridge National Laboratory, Oak Ridge TN USA
The Computational Sciences and Engineering Division (https://www.ornl.gov/division/csed) in the Computing and Computational Sciences Directorate at Oak Ridge National Laboratory (ORNL) is seeking a senior scientist to lead a world-class research group in Experimental Quantum Computing and Sensing within the Quantum Information Science (QIS) Section. The QIS section includes more than 25 full-time scientists carrying out interdisciplinary, collaborative research in fundamental and applied quantum computing, communication, and sensing. With substantial institutional investments in equipment and facilities, as well as recent and expected increases in federal funding from the Department of Energy (DOE) and other federal agencies, the Experimental Quantum Computing and Sensing group is positioned to experience rapid growth. Building on this solid foundation, the successful candidate will develop capabilities in the group to address key quantum sensing and quantum computing R&D targets, from foundational principles to device engineering, fabrication, and implementation.
Research Computing Manager, Barts Cancer Institute - Queen Mary University of London, London UK
We are looking for a highly motivated individual who is outcome driven for a role as the Research Computing Manager specific knowledge of the NHS Data Security Protection Toolkit, ISO27001 and Cyber Essentials Plus. The post supports clinical trials as well as supporting lab and core facility research equipment that staff and students carry out towards achieving the objectives as set out in the FMD Research and Education Strategy. This post also has line management responsibilities and is in charge of the day to day running of the institutes client and server infrastructure located at Charterhouse Square and external sites.
Manager, Clinical AI/ML - Pfizer, Various and Remote USA
We are seeking a highly motivated individual to work at the interface of machine learning (ML) and Quantitative Systems Pharmacology (QSP). QSP is a discipline that uses multi-scale, mechanistic mathematical models and disease platforms to enhance the robustness and quality of decision-making from exploratory research through clinical development. The successful candidate will work to combine existing or novel QSP models with deep learning for clinical applications. The candidate will help us derive insights from Pfizer’s proprietary data and external data to develop a deeper understanding of physiological systems and diseases. The goal is to generate mechanistically driven hypotheses focused on precision medicine approaches. The candidate will partner with clinical experts, AI scientists, biologists, and clinical and quantitative systems pharmacologists to inform clinical study design decisions, including endpoint selection, individualized dosing strategies and/or patient stratification.
Associate Director Bioinformatics - Spatial Genomics, Pasadena CA USA
You are an experienced bioinformaticist who has team/group-leader experience and welcomes the opportunity to be a hands-on contributor while scaling a small existing team and further developing leadership skills. You are a communicator, collaborator, and a technology geek. You have significant experience in single-cell data analysis, algorithm development for quantitative image and/or sequence analysis, and Python/R coding. This role is part of a cross-functional product development team working alongside members of R&D, engineering, and your bioinformatics & software engineering colleagues.
Director, Bioinformatics Core - Beth Israel Deaconess Medical Center, Boston MA USA
The BIDMC Bioinformatics Core (BBC) is part of the Precision RNA Medicine Core at Beth Israel Lahey Health. The BBC will be tightly integrated with the ‘Omics cores at BIDMC. It is the center for bioinformatics research expertise at BIDMC. We work directly with biomedical scientists across our Network and the Harvard community to implement best practice for analysis, interpretation, visualization, and dissemination of scientific discoveries using high dimensional data. The BBC team focuses on teamwork and we provide a supportive learning environment. You understand the growing need for data driven research. You have a solid track record in bioinformatics service provision, excellence in communication skills and written and verbal reporting. A thorough knowledge of current and upcoming developments in analysis of high dimensional data, genomics and the current developments in bioinformatics are essential.
Lead HPC ( High Performance Computing ) and Research Computing Engineer, Office of Information Technology - University of Nevada, Reno, Reno NV USA
The Lead HPC and Research Computing Engineer works with the Cyberinfrastructure Director to realize institutional strategic objectives, collaborating with faculty committees and other IT personnel to provide and evolve technology services that enable advanced research at the University.
The Lead is responsible for leading design, implementation, and support of the University’s central research computing infrastructure. This includes HPC clusters, interactive computing hosts, large-scale storage systems, advanced networks, and associated management and monitoring infrastructure.
Manager, Infrastructure & Software Development, Genome Sequence Informatics - Ontario Institute for Cancer Research, Toronto ON CA
The Infrastructure Manager leads a multidisciplinary team of software developers to create and maintain the Genomics production infrastructure that analyzes all genome sequencing data generated at OICR. The team develops software for running, monitoring, tracking, and debugging bioinformatics analysis, quality control, reporting for internal and external stakeholders, our laboratory information management system MISO and associated software, among other services and facilities. You will lead the design, execution, and maintenance of these systems, ensuring conformance both to sound software development and DevOps principles and, when necessary, standards such as ISO15189 and accreditation bodies such as IQMH/CAP. Together with the Managers of Analysis and Cancer Genome Interpretation, you will set and facilitate GSI operational goals and objectives. This role sits within the Genome Sequence Informatics (GSI) core group and reports directly to the Director, GSI.
Head of Information Services and Infrastructure Support - The University of Edinburgh, Edinburgh UK
A key member of the School Management Group the Head of Information Services and Infrastructure shall be responsiblefor the organisation, management, development and delivery of high quality services across our Information Technology, E-learning and Buildings & Facilities services teams. The role is primarily focussed on management and coordination; however, in-depth technical expertise is required across a wide range of technology disciplines. The ability to build positive, supportive and close working relationships with academic and professional services colleagues is a must and the post-holder will manage the delivery of a wide portfolio of services across a range of support levels, liaising with a variety of both internal and external stakeholders to the school/university.
Engineering Lead – Scientific Computing Platform - Astrazeneca, Cambridge UK
The Scientific Computing platform (SCP) is a foundational capability for HPC and scaled computing solutions. Embedded within the Research D&A organisation it is central to analytics products focused on computational chemistry, imaging, multi-OMICs, structural biology, data science and AI. The SCP Engineering Lead will both lead an agile engineering team and set the technical strategies to meet future scientific computing needs, where machine learning and AI are increasingly playing a major role in drug discovery at AstraZeneca. We are seeking a highly motivated and dynamic engineering manager with a track record of empowering people and fostering an inclusive team culture where collaboration and engineering excellence thrive. You will bring a wealth of experience in the design and operation of scale-out enterprise platforms, and have the expertise to lead a globally distributed agile DevOps team.
Research Infrastructure Lead - University of Melbourne, Melbourne AU
In this role, you will provide high quality support to research infrastructure development, and the strategic consideration of research infrastructure within grants, partnerships, major initiatives, and commercial opportunities. You will work collaboratively with colleagues across RIC, Chancellery (Research and Enterprise) and our Academic divisions. You will lead and support strategically important, high value funding and commercial development opportunities for the enabling infrastructure that underpins delivery of the University’s high quality research outcomes. You will further contribute to the portfolio of activity by our team by contributing a deep knowledge of the research infrastructure landscape, both within and external to the University.
Manager, Advanced Applications - Purdue University, West Lafayette IN USA
As the Senior Research Operations Manager, Scientific Applications you will lead a team of computational scientists to provide technical assistance to the research community of Purdue. This includes facilitating access to Research Computing resources, providing training, documentation, and responding to tickets of requests and troubleshooting. You will provide technical leadership in designing, implementing, and operating the supporting components of a high performance computing environment. You will develop and manage stakeholders’ communication including, assuring appropriate communications and coordination with management, customers, and internal and external departments. You will represent the team on advisory, policy and project committees, and provide technical consultation and support. You will be responsible to supervise professional and student staff.
Product manager - high performance computing - Target, Brooklyn Park MN USA
The High-Performance Computing (HPC) Product Manager will maintain and build products ranging from real-time data streaming to neural computing. Your products will enable teams at Target to stream, filter, transform, and analyze high-bandwidth data in real-time, and provide tools for data engineers and other team members to analyze and take action on their data. You will research the capabilities of next generation computer hardware, architectures, and algorithms in order to: build enterprise grade, efficient products and provide guidance on building scalable, fully utilized infrastructures.
Quantum Specialist – Quantum Chemist - Deloitte, Various, USA
Given the potential for quantum technology to drastically improve computational abilities in chemistry and biology, you will help Deloitte stay on the cutting of edge of what is possible for our clients. You will be responsible for driving technical exploration, research, and development of quantum use cases that relate to computational biology. Additionally, you will lead conversations with researchers, clients, and our partners in the quantum ecosystem (e.g., hardware/software vendors, start-ups).
Director of Data Engineering - BenchSci, Remote CA or US or UK
We are looking for a seasoned Director of Data Engineering, who lives and breathes tackling data challenges to join our growing team. This is a challenging, impactful, and highly collaborative position. Reporting to the Sr. Director of Data Engineering, Machine learning, and Bioinformatics, you will be responsible for spearheading our Data ingestion and modeling initiatives, working across a wide variety of biomedical data, and helping the team to extract scientific insights.
Principal Quantum Software Engineering Manager – Compiler and Runtime - Microsoft, Redmond WA USA
You will be leading a team of quantum software engineers building a first generation of compiler and runtime for executing quantum programs on current and future quantum systems. You will empower and grow your team members through coaching, career development, and guidance. In partnership with program managers and internal and external software and research teams, you will define and build a sustainable and versatile software stack to support a variety of quantum processor architectures and programming languages, including Microsoft’s quantum programming language Q#. You will oversee design reviews, set software engineering standards, define engineering guidance, and ensure high quality delivery. You will drive and accelerate communities of customers and partners and build an open-source development ecosystem.
Senior Manager, Product Owner - Research Informatics - Moderna, Cambridge MA USA
This role is an exciting opportunity to be part of Digital for Research Product team playing a crucial role in managing and delivering workstream prioritization, customer success, and serving as the front-line support for Research Informatics issues. You will triage issues between the customer facing and engineering teams with contemporaries operating in a SCRUM methodology. You will be a practitioner of Agile, an expert in requirement gathering practices, place proper use and training of applications as priority, and be able to articulate the Business Problem to be solved for.
Program Manager, Strategic Initiatives in AI - University of Michigan, Ann Arbor MI USA
The AI lab advances the work of its more than 25 faculty members by creating a welcoming and supportive research community, providing engagement with collaborative strategic initiatives, and supporting education and training of its 100+ affiliated PhD students. The manager for strategic initiatives in AI is responsible for identifying, developing, managing, and evaluating a portfolio of signature projects and research interests focused on key areas of our member’s research including: machine learning, natural language processing, computer vision, and decision making. This will involve coordinating closely with the office of tech transfer (or wherever the business engagement office people landed) and faculty members in the AI lab. The Manager for Strategic Initiatives reports to the Director of the AI lab.
Software Development Manager, High Performance Computing (New Service) - AWS, Boston MA or Denver CO or Bellevue WA USA
We build NICE EnginFrame, AWS ParallelCluster, and the overall experience for customers building some of the largest HPC and distributed ML clusters in the world, while at the same time empowering research scientists and engineers to dynamically scale their HPC workloads to enable scientific and engineering breakthroughs. We enable a broad set of applications for computational fluid dynamics, weather modeling, molecular dynamics, seismic modeling, and machine learning. You’ll be leading a new team in Boston and will be part of a distributed engineering team across US and Europe. The ideal candidate will have strong distributed systems design and software engineering experience, Linux/Unix and networking fundamentals, and a passion for AWS technology.
Research Informatics Director - BC Children’s Hospital Research Institute, Vancouver BC CA
As a senior leader at the BC Children’s Hospital Research Institute (BCCHRI), the Research Informatics Director will provide oversight, leadership, and guidance in the planning, management, and execution of the mentorship and training program. This position will responsible for developing strategic plans and systems for research informatics, working collaboratively with partners to ensure that research is aligned and integrated into plans for clinical care delivery and education, during a critical time of strategic growth of the research institute. The Director will also oversee the strategic direction and operations of the biostatistics and data management cores to support the clinical research activities at this site and beyond. The Director will provide leadership and direction, oversee the acquisition and deployment of cost-effective IT infrastructure solutions and software systems that adequately support and enhance research informatics, information technology, high performance computing and analytics.
Manager, Clinical Informatics - Provincial Health Services Authority, Vancouver BC CA
The Manager, Clinical Informatics reports to the Director and is responsible to oversee the day-to-day management, operations, and evaluation of the clinical informatics services. The role leads the team in the transformation of clinical practices, processes, documentation and reporting enabled by the integration of technologies to enhance care quality, safety and efficiency. Their goal is to successfully advance the meaningful use of electronic health records (EHRs) in acute, community and primary care. Collaborating across and within the health organizations, the position provides strategic, tactical and operational EHR expertise to the clinical teams and leaders. The position acts as the senior clinical informatics strategist and subject matter expert that translates and prioritizes clinical requirements into the selection, design, build, implementation, maintenance and evaluation of clinical system technologies to enable person and family-centered care. The role also leads the planning, budgeting, scheduling, recruiting, training and performance of the clinical informatics team.
Scientific Computing Platform: Technical Lead, HPC Applications & Workflows - AstraZeneca, Cambridge or Macclesfield UK or Gaithersburg MD or Waltham MA USA or Toronto Canada or Gothenburg Sweden
We are seeking a passionate, HPC applications specialist to join the team as a Technical Lead with responsibility for applications strategy, delivery and support. The ideal candidate will have extensive hands-on experience making an impact with HPC technology, be able to relate to the scientific community and also play a leading role within the platform team. The HPC applications landscape is continually evolving. You will be responsible for sourcing the optimal technologies to deliver industry-leading capabilities, including application build frameworks, containerised applications and cloud software-as-a-service. Automated application deployment is a key feature and the Technical lead for Applications will have oversight of the end-to-end application process, from creating build templates and testing through version control and automated deployment.