RCT #181 - Positioning, Marketing, and Other Bad Words. Plus: Onboarding instead of sink-or-swim; Making your next week earlier with an hour of planning; Visually communicating software design; HPC containers; and HPC desktops
I want to close our discussion that started way back in #176 about this flywheel we want to keep going, by going back to the start.
In #176, I talked about how key it is to nurture our best clients, the clients who:
- Produce high-impact work as a result of their work with us
- Our VPRs pays attention to
- Is influential with fellow researchers, funders, the institution, and other stakeholders
- Does work with us that we can sustainably support with non-heroic amounts of effort
- Speak highly of our teams
- Advocate for our teams, or could conceivably do so if helped to do so
Then we talked our way around the flywheel. In #177, we talked about doing the highest bang-for-buck work to maximize our research impact; in #178 we talked about how the bar for the services we offer researchers should be that they’d be willing to pay for them if they had to; in #179 we talked about how success stories from those high-impact projects are the best and most effective form of advocacy; and in #180 we talked about how doing all those things would help us with the first of the two big problems we face internally: fundability and staffability. (The second is our responsibility as leaders).
So how do we do more of this highest bang-for buck, high research impact work that researchers really value and will generate strong success stories?
Assuming we’re already doing some work like that for our best clients, the simplest way do to more isn’t to about internal operations of the team, it’s more outward looking.
The simplest way to get more of this high-impact, highly valued work is to find more work like we’re doing for our best clients. And that means finding more clients like those best clients.
Part of that means understanding those clients, and what our teams do for them. That means talking with them (#158).
One might think that we already know what we do for those researchers - our teams are the one doing it, after all! But the vast majority of teams I talk do don’t actually know what parts of that matter the most to the researchers, or why that is.
Understanding our best researcher clients and what we do for them means going to the outrageous length of actually talking with them. It means asking questions like:
- What’s the alternative to working with us? Hiring another postdoc, buying and running a system, contracting out to a commercial vendor, doing a different type of project… what would they do if we weren’t around?
- Why did they choose us instead of one of those other options?
- What was the basic challenge they faced with this research project, and how did our services help them fix that?
- What was the most important way our work benefited them?
- What were they worried about before working with us, and how did those worries get resolved?
- What are they most satisfied with? What are some examples of that?
- What could we do better at? What are some examples of that?
- How’s our “service” - how are we in terms of communications and responsiveness? Is there any way we could improve?
- Would you be willing to recommend us to others? Are there other groups you think we should talk to that we could help the same way we’ve helped you?
Once you have the answers to those questions from a half-dozen of your best clients, there’ll start being some patterns that you can use to find more work like some of the best work your team is doing. Because “clients like those best clients” likely doesn’t mean “in the same sub-sub-discipline of chemistry as Prof X”. It means people who need similar types of problems solved.
If you're hearing again and again that your team is the alternative to hiring a postdoc, then you can start communicating that working with you is a way to keep their trainees focussed on science, and you could start (for instance) approaching computational groups who are having trouble filling postdoc positions.
If you keep hearing that the alternative to working with you is doing less computational work, you can start communicating that “building out their computational research programme” is a key benefit of working with you, and approach groups that are doing a little but not much computational work currently.
If you’re hearing that the alternative to your services is a commercial service, you can try to get a talk about your services into a workshop on campus that talks about those commercial services.
If you keep hearing that the biggest help your group provided was faster “time-to-science”, you can start communicating that, and start targeting researchers in highly competitive fields.
And all of this communication goes much better if you use the actual language your best clients used to describe the benefit.
Here’s the thing. Identifying the groups you helped the most and choosing other people in that same situation is called “market segmentation”. Putting together some material - a talk, an email, a blog post - describing how you help that segment, especially while being aware of the alternatives, is called “positioning”. And finding out where people in that segment are and finding ways to communicate with them are the first stages of “marketing”.
These aren’t dirty words. They don’t describe tawdry activities that are beneath us and would sully our teams’ good name.
These are steps in finding out who we can best help, and communicating in ways that make sense to them that we can in fact help.
These are steps in making sure we’re having the most positive impact on research in our community as possible.
They’re also steps in improving our own performance in ways our best clients actually care the most about. If we could use some improvement in communications with our clients, but what our best clients actually care about is getting results quickly, spending project time writing up periodic status reports to send to the clients would actually hurt our most important feature.
(“But what if our other clients would really like those reports?” Look, we care for and respect all of our researcher clients equally as human beings. But our goal is to advance research in our community as far as possible given the constraints (including resource constraints) we face. That means optimizing how we do things for the work that has greatest impact. Different groups want different things, and we can’t make everyone happy. We owe it to research in our community to focus as much optimization effort on possible on the work we do that has the greatest impact.)
By finding out what really matters in the projects that have the greatest science bang-for-buck, we can do more of it, improve how we do it, and better communicate how we help to more people who have similar work. This makes success stories easier to gather, advocating for our teams easier, and makes communicating our value to the institution easier. It keeps that flywheel going around, faster and faster.
And it’s not hard. We just need to talk to people and be willing to change how we talk about the work of our team.
This is a long weekend holiday in Canada, so apologies for getting this out late and for being a little light on the roundup. If this was a long weekend for you, I hope you enjoyed it! If you have one coming up, I hope you enjoy that!
And now, on to the roundup!
Managing Teams
Over at Manager, Ph.D., in issue #173, I talked about how to tell if you are you accomplishing things, or you are just busy.
In the roundup were articles on:
- Giving feedback
- Coaching skills at work
- The infinite hows (vs the 5 why's)
- First, understand; and
- Stop people pleasing.
Technical Leadership
What causes new engineers to “sink or swim”? - Lizzie Matusov
We talk a lot here about onboarding, e.g. - making an onboarding plan (#141) as one of the early steps of hiring, and beginning hiring with the end in mind (#135) - and supporting our teams by finding out what they need in one-on-ones and then coaching them as needed.
In this article, Matusov summarized a paper that that took survey data from 104 participants of early career new software developers that had just completed onboarding. The results weren’t great:
Clarity in role or job assignment was critical to early engineer experience; 38.5% of engineers did not know what to work on during onboarding. The highest-reported impact of this was distress and decreased productivity. Management and team support was a top factor for onboarding success. 74.3% of engineers felt their manager was invested in their development, and 85.71% of engineers felt their team was invested.; 19.8% of engineers were not paired with a manager when onboarding. The top areas of improvement recommended by new engineers were training and work distribution and planning methods.
Hiring takes a lot of the team’s time, and it’s so disappointing to see teams fumble this task - arguably the most important thing a team does - right when it’s nearly over. Onboarding is part of the hiring process; I argue it should be one of the first things we figure out in the hiring process, because it sheds light on what skills are absolutely essential and what the new hire can be taught.
We want our new hires to succeed, and to feel successful, relatively quickly - don’t neglect onboarding!
Managing Your Own Career
How to invest an hour now to make next week a bit easier - Loleen Berdahl
Berdahl talks about spending some time at the end (or start) of the week to take things off our calendars by bowing out or cancelling things, making sure more of the things that stay on our schedule are productive, and stay in a bit better control. I particularly like Berdhal’s scripts for cancelling unnecessary meetings or “suggesting” agendas for meetings at risk of being unproductive time wastes. Definitely worth the quick read.
Research Software Development
Visually Communicating Elements of Software Design - Rafael Mudafort, Better Scientific Software
Communicating Software Design- Rafael Mudafort
Mudafort writes about diagraming software design; the BSSw post is mostly about UML, which I have some feelings about, and Mudafort’s site below has a bunch of good links to diagraming tools (including diagram-from-code) tools. We’ve talked before about how documentation is information, not active knowledge (#149), but good documentation (and especially diagrams) make it much quicker to bring information into people’s heads where it can become knowledge. So knowing what diagraming tools are out there that can help with the visual documentation and communication of design is useful.
(BTW, is any one else really annoyed that here in the common era year two thousand twenty four, where we’re mostly using tools like VSCode as editors, we still have to draw ASCII art programs instead of embedding SVG diagrams in comments? Guess that’s a rant for another time).
Research Computing Systems
The HPC Containers Survey - Containers Working Group
Interesting survey of 202 people, largely with some significant amount of container experience, on how they’re using containers in HPC.
The tools being used are overwhelmingly on HPC systems are either Singularity/Apptainer, Docker, or Podman, in that order. On people’s personal systems, however, Docker is the clear winner.
Even for people using singularity, it seems like Dockerfiles are how most people are defining containers, with Singularity a respectable second. A lot of people are using space or easy build in their containers.
It sounds like most people aren’t pushing images, just publishing recipes, which is a bit of a shame; of those who are, people typically use Dockerhub, GitLab or GitHub.
While containerization is mostly used for applications, it seems like a lot of people are also using them for developer environments, for the sort of thing people used to spin up vagrant VMs - that’s interesting.
There’s more people than I would have guessed who build containers for multiple architectures - a minority, but still - and more than half of respondents use CI/CD for containers, which I find heartening although the survey organizers were disappointed it was as little as that.
Emerging Technologies and Practices
Use Cases for High Performance Research Desktops - Henschel et al, 3rd Combined Workshop on Interactive and Urgent High-Performance Computing at ISC 2024
(Disclaimer - my current day job is at a company that sells both GPUs and software for this use case amongst others, but this paper doesn’t really mention either so I don’t see much of a conflict of interest here)
There’s a few trends coming together - increasingly interactive and complex workloads, plus workloads that require large amounts of data and/or specialized hardware and/or control of sensitive data - which are re-igniting interest in different kinds of hosted desktops on high performance systems. AWS, for instance, is touting how easy it is to do exactly this with the NICE DCV protocol, aimed very explicitly at HPC-type applications, so they presumably see this as an area of growing demand.
But it would be nice if we could also do this on our own systems.
In this article, the authors talk about the various use cases for this kind of service, where it fits into an HPC stack, and some experiences. They talk about the pros and cons of using something like OpenOnDemand, They talk about some things they’d like to see, such as deeper integration of the HPC system scheduler into the desktop, nicer GUI tools, and the development of more of a community and open source tools.
Random
Fortran at the edge with Fortran on Cloudflare Workers.
An interactive C/C++ preprocessor macro debugger.
Drawing circles with only integer shifts and adds.
When your cable management becomes creature management - sloth gets caught in server rack in Brazilian university data centre.
That’s it…
And that’s it for another week. If any of the above was interesting or helpful, feel free to share it wherever you think it’d be useful! And let me know what you thought, or if you have anything you’d like to share about the newsletter or stewarding and leading our teams. 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 in the email edition; the full listing of 154 jobs is, as ever, available on the job board.
Senior Investment Manager – Digital Research Infrastructure at AHRC - Arts and Humanities Research Council, Swindon UK
The successful candidate will be responsible for leading allocated activities within AHRC’s Programmes division on Infrastructure. This includes overseeing the development and implementation of funding schemes and initiatives, as well as focusing on strategic areas within the infrastructure portfolio. Collaboration with other Team Heads and Senior Investment Managers within and across AHRC teams is essential to coordinate activities effectively. The role also involves providing input into the strategic direction of the team and research programmes, managing existing schemes, and developing and delivering new initiatives.
High Performance Computing Project Manager - Atomic Weapons Establishment, Reading UK
AWE is looking for an experienced and adaptable Project Manager to lead the delivery, installation and commissioning of a new High Performance Computing (HPC) capability. The Project Manager will also be responsible for reporting to the accountable Senior Project Manager for ensuring the obsolescence management of future HPC, Storage, Networks and Workstations capabilities in accordance with the customer’s service level agreement. Your focus will be on taking ownership of assigned projects, addressing any technical and resource issues to mitigate risks, and driving the delivery forwards to time, cost, and quality. You will work closely with the HPC team to ensure capability, the availability of networks around site, and work stations etc. As the Project Manager, you will be the main point of contact for all suppliers, the construction team, and sub contractors. This is a fast paced and interesting area of the business, you will need to be both reactive and proactive, thinking pre-emptively on equipment obsolescence and renewal. This is a unique opportunity to make a real difference to the safety of our nation.
Centre Manager, Data Science - Queensland University of Technology, Brisbane AU
The Centre Manager provides leadership and management of the Centre’s core operational activities, working closely with the Director and other senior leaders to ensure the efficient and effective delivery of Centre’s vision and objectives. The Centre Manager will lead and have responsibility for managing the operation of the Centre, delivery of administrative services, project delivery support and all operational matters. The position has operational responsibility for the Centre’s budget (including operating and discretionary budgets) and collaborates with share services staff across the Faculty and University to execute the effective operations of the centre.
Facility Research Manager, Mass Spectrometry Unit - Western Sydney University, Sydney NSW AU
Westerns Research Infrastructure team is seeking an experienced Facility Research Manager to join their Mass Spectrometry Unit. This unit plays a vital role within the University, supporting various research activities across molecular sciences, biology, chemistry, forensics, and biophotonics. The Facility Research Manager will oversee and maintain the operational performance of the Mass Spectrometry Facility and its instrumentation. Responsibilities include managing the facility, supporting high quality research, providing training for academic and HDR student users, collaborating with Research Services to generate revenue through the provision of sample analysis for external clients, driving innovative research approaches, participating in technical support and committee meetings, and contributing to future strategic planning. Additionally, the manager will handle budgeting, stakeholder engagement, sample analysis, and compliance documentation.
Engineering Manager, GPU Platform - OpenAI, San Francisco CA USA
As we scale the number of GPUs, number of users, and size of OpenAI, having a team dedicated to the infrastructure to support is crucial. This EM will be responsible for one of our compute teams, GPU or general. They will be responsible for the design, deployment, and management of a massive compute fleet that can grow to meet our business needs.
Biomedical and Clinical Data Informatics Research Manager - Nuvance Health, Danbury CT USA
This complex and multifaceted mid-level manager role demands a highly skilled and experienced individual to lead and manage all aspects of biomedical informatics and clinical data for research protocols for the Department of Research and Innovation. The ideal candidate will possess in-depth expertise in analyzing patient molecular data, combining it with Electronic Health Records (EHRs), and applying AI and ML methodologies for statistical modeling and prediction of outcomes. He/She will also have exceptional managerial skills to oversee data coordination staff collaborate across multiple departments, and support clinicians and researchers. The manager will also oversee and support clinical and investigator-initiated research initiatives related to data, collaborating closely with clinicians, fellows, and residents to translate ideas into actionable projects. The role will utilize project management skills to research workflows and implementing efficient data operations.
Software Engineering Manager, ML HW-SW Codesign - Meta, Sunnyvale CA USA
Meta Reality Labs (RL) is the world leader in the design of virtual and augmented reality systems. Come work alongside expert engineers and research scientists to create the technology that makes VR and AR pervasive and universal. Join the adventure of a lifetime as we make science fiction real and change the world. We are looking for a Software Engineering Manager to support a team of HW-SW Co-design engineers and research scientists. The team would drive HW aware optimizations for CV and LLM workloads running on AI accelerators. The span of work involves model optimization, quantization and network architecture search. The team works in collaboration with ML compiler, ML architecture and ML enablement teams and XFN partners to enable highly optimized solutions for AR products. The ideal candidate will have expertise in supporting a full stack model optimization for AI Accelerators.
Manager, Data Science, PROOF Centre - University of British Columbia, Vancouver BC CA
The Manager of Data Science is responsible for leading, overseeing and managing all computational aspects of research carried out at the PROOF Centre of Excellence. This includes statistical considerations, data management, management of computational staff and students. The incumbent will, develop, and conduct statistical and data mining analyses to identify and evaluate predictive, diagnostic, and prognostic biomarkers for various health outcomes. Major responsibilities include being part of the PROOF Centre of Excellence management team; designing and developing data analysis software; managing the Centre’s large and growing collection of molecular data; performing statistical analysis and modeling of big data, including various omic data (e.g., transcriptomics, proteomics, metabolomic, and epigenetics measurements); writing statistical and data analysis plans, reports, research proposals, and publications; and supervising junior computational staff and students.
AI & ML Software Engineering Manager, TR Labs - Thompson Reuters, Toronto ON CA
Thomson Reuters Labs is seeking a AI & ML Software Engineering Manager with experience leading a team of engineers to build artificial intelligence (AI) powered applications for legal drafting and review. As a member of Thomson Reuters Labs, you will have a direct impact on the world by creating new and innovative products that improve the speed and quality of legal practice, transactional law, and more.
Data Science Learning Associate Director - AstraZeneca, Barcelona ES
Are you ready to be a part of a dynamic team that ensures the long-term success of our Data Science Academy (DSA), As the Associate Director, you will work closely with the Data Science Learning Director to deliver an impactful and innovative educational program in data science and related areas, focusing on the R&D community. This is an opportunity to play a key role in supporting adoption of cutting-edge data science methods across R&D, pushing the boundaries of science and making a difference to patients.
Director ITS Research Computing - Rochester Institute of Technology, Rochester NY USA
Reporting to the Chief Information Officer, you will work closely with senior leaders, including the Vice President for Research, deans, and others to align research computing with RIT’s strategic goals and priorities. You will also lead a dynamic team who provides research computing and data management services, support, and consultation to the RIT research community. In addition, you will engage with faculty researchers across disciplines to understand their research computing needs and challenges, and to identify and implement solutions. The successful candidate will be a strategic thinker with an open and collaborative style who fosters innovation, teamwork, employee development, and operational effectiveness.
Product Manager, Bioinformatics - Genomics PLC, Cambridge or Oxford or London UK
Are you ready to bridge the gap between cutting-edge science and product management? We are seeking a dynamic and driven individual to join our team as a Product Manager specialising in bioinformatics. This is your chance to leverage your technical expertise in a collaborative environment where you'll play a pivotal role in revolutionising precision health products. Reporting to the Lead Product Manager, you'll immerse yourself in the work of scientists and engineers, seamlessly integrating pioneering science into our products. Your role will extend to building our sample and data processing applications more broadly.
Lead Data Scientist / Lead Theoretical Modeller / Lead Software Developer - UK Atomic Energy Authority, Culham UK
The Computing Division at UKAEA plays a vital role in fusion reactor research, covering HPC, data solutions, algorithm development, and AI. This role, within the plasma simulation group, applies modern computational methods to areas of plasma physics. We collaborate closely with specialists in the plasma division and are aiming to expand partnerships with institutions in the US and Europe. Key research areas include developing new simulation capabilities, utilising machine learning for reactor design, and deploying uncertainty quantification tools. Candidates need a background in plasma physics or a closely related discipline, plus experience in scientific computing and/or knowledge of machine learning. The roles may involve the opportunity for an extended secondment to a partner institution.
Data and AI Senior Manager - Accenture, Melbourne or Sydney AU
You will work with our comms clients to build and deliver their Data and AI strategies. In addition to key client relationships, you will also be involved in significant engagement across our business, at multiple levels. You will be someone who can identify opportunities for Data and AI and build capability with key teams internally.
Executive Director, Health Statistics and Informatics - Northern Territory Government, AU, Darwin AU
Provide strategic leadership to the Health Statistics and Informatics branch, including oversight of routine reporting of statutory registries, internal/external academic collaborations, Health Informatics, Health Economics and routine reporting of health statistics.
Director, Bioinformatics Core - Beth Israel Lahey Health, Boston MA USA
The Bioinformatics Core Director will have strategic and tactical responsibility for the operations of the core, consultation, recruiting, overseeing core support staff and provision of leadership in developing core resources and providing research support and training for research faculty and staff at BIDMC. The Core Director will lead a team that develops and applies bioinformatics workflows for standard and custom data analysis across a broad range of technologies, such as single nuclei sequencing, spatial transcriptomics, genome variant analyses, transcriptomics or epigenomics. The Core Director is expected to create deliverables that could serve as standards for quality and innovation in broader communities, building informatics tools for data management, omics and imaging analyses within the reality of clinical data integration.
Director of Bioinformatics - Southern Research, Birmingham AL USA
The Director of Bioinformatics will report to the Chief Data Officer. In this role, you will be responsible for overseeing the development, implementation, and maintenance of bioinformatics strategies and infrastructure to support cutting-edge research. You will work with external biobanks, clinical sequencing laboratories and clinical data health ecosystems to aggregate and assimilate molecular datasets and analysis pipelines in the cloud to support a bioinformatic research community. The Director of Bioinformatics will work internally with SR IT, Data Analytics, Medical Informatics, and product teams to develop a clinicogenomic database; and, externally with pharma sponsors to develop collaborative research projects in support of discovery and development programs.
Bioinformatics/Data Science Lead (Senior Manager/Director/Senior Director) - Curve Biociences, San Mateo CA USA
We are looking for a bioinformatics/data science lead to advance Curve’s biomarker discovery capabilities, NGS bioinformatics pipelines, and clinical test classifiers. Your expertise in biology, genomics, and data science will propel our platform development and discovery efforts leading to the successful launch and adoption of new blood testing products for chronic disease patients with unmet medical needs. This role is expected to initially provide hands-on individual contribution but can evolve to have functional leadership for our bioinformatics and data sciences strategy, teams and culture.
[Director, Statistics](Director, Statistics) - Abbvie, San Francisco CA USA
The Director, Statistics provides scientific and statistical leadership for assigned clinical development projects. A highly empowered, visible and collaborative role, the Director works in partnership with clinical and regulatory experts to advance medicines to our patients. Lead the statistical support for one or more clinical development projects through own efforts or those of a team. Lead statistical strategy for project development and regulatory submission. Direct and review the development of design, analysis and reporting for clinical or other scientific research programs. Review Protocols, statistical analysis plans, and statistical programming plans. Represent function/department on project team(s) to provide statistical input to compound/drug development and drive alignment with functional management. Partner with other functions (Clinical, Regulatory, Patient Safety, or GMA) to create development strategies for assigned projects. Represent DSS on data monitoring committees. Build interdepartmental relationships.
Product Manager, HPC & Computational Science Environments - Novartis, Cambridge MA USA
The Scientific Data and Products (SDP) group in RX builds and applies excellence in product and data management to continuously improve the impact and value of software and data to Biomedical Research. We deliver intuitive, intentional, and integrated software solutions that create a frictionless user experience. As Product Manager Computational Science Environments, you play a leading role in defining the future of our Research Dry Lab – a fully integrated combination of high-performance computing (HPC) environments, internally built systems and industry standard software, with a focus on applications that comprise the computational environments for community of data and computational scientists engaged in Computer-Aided Drug Discovery (CADD), Structural Biology, Bioinformatics, Image Analysis, and Modeling & Simulation.
Manager, Digital Solutions - Canadian Institute for Health Information, Toronto or Ottawa ON CA
We are an independent, not-for-profit organization and together with our partners we provide essential information on Canada's health systems, enabling decisions that lead to healthier Canadians. CIHI, through the Hub Program, is continuing along its path to create a more unified, efficient, and adaptive approach to how data is processed, prepared and reported. The Manager, Digital Solutions is a critical role as it is responsible for overseeing the implementation of this multi-year program of work, collaborating across CIHI’s business areas and providing strategic advice to senior executives to guide the successful and timely completion of program objectives.
Facility Manager, UW Nuclear Magnetic Resonance Facility - University of Waterloo, Waterloo ON CA
The University of Waterloo Nuclear Magnetic Resonance (UWNMR) Facility Manager is responsible for all aspects of the UWNMR facility operations. The position is accountable to the Chair of the Department of Chemistry to strategically lead facility operations, implement new systems, processes and strategies, as well as management and administration of the state-of-the-art facility located in the Department of Chemistry. As a core facility on campus the facility participates and supports research programs within the Faculty of Science, WIN (Waterloo Institute for Nanotechnology), Engineering, IQC (Institute Quantum Computing) and Velocity, as well as the initiatives in the University of Waterloo’s Strategic Plan.