Research Computing Teams #146, 19 Nov 2022
One of the things I wrestle with a bit with the newsletter is trying to cover the range of topics that research computing and data managers need to think about without being overwhelming.
But we have genuinely challenging jobs, that span a range of concerns. I gave a presentation about this earlier in the year, but I haven’t quite talked about it the same way here.
We have three main areas of concern which we have to make sure we’re paying attention to - the people in our team (individually and collectively), the work output/products our team produces, and the processes by which we operate. All of those need careful tending to, both for the future (nurturing growth and development), performing regular maintenance care, and dealing with occasional urgent matters. And they’re all essential; people firing on all cylinders but held back by incoherent processes and working on the wrong outputs aren’t going to have the impact they could.
I like a gardening metaphor for this, because it reflects the fact that nurturing growth takes sustained effort, where as blight and weeds can spread with shocking quickness if allowed to do so (and takes much more effort to fight back than it does to prevent). It’s also true that if the teams, processes, and products are healthy and vigorous, they can make it hard for a weed to find purchase.
In steady state, we want to be spending most of our time in the top 2/3 of the diagram - nurturing our people and team, maintaining lines of communication, and making sure our work outputs are those that have the most impact. In any given week, we want to make sure we’re spending much of our ongoing work on maintenance efforts across all three columns, and putting some effort into targeted nurturing.
If we’re spending a lot of time putting out weed or blight outbreaks, that’s normally a symptom that there’s not enough maintenance care happening. Sometimes the urgent issues have an external source, of course; we’re being roiled by some outwardly driven change. But more often they’re internal. And the under-maintenance isn’t necessarily coming from the column where the outbreak is happening. The process issue may be an issue of the team not communicating well together, or the problem with product quality may stem from processes.
I spend most of my time writing about the people column, and I think that’s appropriate. People are the area probably least familiar to many of us who were trained in highly technical areas. And strong teams of people can better handle (or fix!) poor processes or work product focus, while excellent processes or products can’t counteract people problems.
In the last year or so I’ve been writing more about products in the sense of strategy - what is the most impactful work we can be doing? What are the most important work products we can be producing, and how do we decide which to drop and which new ones to start on?
Whereas I don't really write nearly enough about processes. They’re important, even though as researchers and technologists we tend to downplay them.
We shouldn’t be creating process for its own sake, of course. But this isn’t about creation so much as ongoing development, just like people and products.
We have countless unwritten processes in our team, and we can’t really improve them in any meaningful way until we document them. This is just like wet lab protocols; if you haven’t recorded the steps you took, how can anyone reproduce them? How can others be onboarded into doing that work? And how can the processes be incrementally made better, or compared to other approaches?
Process is the mechanism by which craft work becomes professionalized, becomes automatable, becomes something that can be handed off. The first few times your team does something, it’ll still be in the mode of searching for a good way of doing things. Once it’s found an initial good way, that’s something that can be usefully turned into a process, and documented with not just the steps taken, but the goal of that process, and why this way works. Checklists work.
On the technical side, we as a community tend to pretty good about making sure everything’s documented, that there are scripts for automating tasks, etc. But for more people-oriented processes we’re often not great. If we find ourselves saying things like “Francis isn’t here today, and they’re the person who handles that; we’ll have to wait”, that’s a pretty good indication that there are important undocumented processes. It can be a work task, or how meetings are run, but processes bring clarity.
One failure mode is that unless they’re documented alongside why things are done via that process and what a good result is, they can become ossified.
But when that context is included with the processes, and permission is given to try doing things different ways and see if that’s better, then it becomes a key piece of continuous improvement. There are really mature tools for thinking about, developing, maintaining, and updating processes - many come from the world of project management (or program/portfolio management), and we can learn from or use them.
What do you think - are there areas where too little (or too much) process have hindered your team? Are there project management tools or approaches you use for keeping track of multiple processes “in flight” in your team? How do you handle documenting not just factual knowledge but procedural knowledge in your team? Let me know - just hit reply, or email me at firstname.lastname@example.org.
PS: I got a lot of great responses last week about our first RCT interview, with Matthew Smith. Are you interested in being interviewed for RCT? There are lots of particular topics I'd like to hear about - you see them covered in the newsletter - but it's also valuable for the community to hear from other managers and leaders and learn from their experiences. Don't hesitate to email me if you're interested! Just email email@example.com.
And now, on to the roundup!
Peer One On Ones: How To Unlock Great Collaboration Across Teams - Lighthouse Blog
One-on-ones are a fundamental tool for developing trusting working relationships with direct reports.
But regular meaningful conversations can always build trust and strengthen lines of communication, regardless of reporting relationship.
Peer one-on-ones are a great and simple way to develop effective professional relationships and communication channels with peers on other teams. Feel free to call them something vague like “check-ins” or “sync-ups” if you prefer.
The Lighthouse blog gives some suggestions - they don’t have to be weekly, for one, even every four weeks or longer is a lot better than nothing. And there’s a great list of possible topics:
- What's one thing we could change about our processes that would help your team?
- Is there anything my team does that your team really likes? Why do they like it?
- What's the hardest thing about working with me or my team? Why?
- What do I not know about your job that I may have an impact on?
- What's your biggest challenge right now for you and your team?
- How can I help make your job easier to do?
- Are there any interpersonal issues between anyone on your team and mine I should know about?
- What could we do together without having to use much budget or other people to improve things for our teams?
(This is a timely article, because I just advised someone who was having some issues with a peer in a different reporting structure, and who wanted to give them feedback. Feedback works much better if there’s already a working relationship and communications. They will take the feedback more seriously, and you can express the feedback in terms they are more likely to care about, if you’ve already had several working conversations. Since this will be an ongoing working relationship, and the feedback wasn’t time sensitive, I advised starting peer one-on-ones with the colleague, and only after a couple of those raising the issue).
Leader as Shock Absorber - Ed Batista
Maybe a couple of decades ago, the idea of a manager or lead as a “sh*t umbrella” became popular; it probably came from a good place, an urge to protect team members from the vagaries of the larger organization.
There’s a pretty widespread understanding now that this just isn’t a good mental model. It’s infantilizing; it is fundamentally built on a lack of transparency; it models the rest of the organization as an uncontrollable, exogenous, force that randomly produces excrement to be handed down; and if the manager or lead guesses wrong about what the team needs to know, it leads to bad and preventable surprises.
Batista’s analogy of a shock absorber, I think, captures the well-intentioned pieces of the umbrella analogy but without the problems:
- A shock absorber cushions the blow; it doesn’t prevent the flow of force but redirects it.
- A shock absorber pushes back in both directions
- A shock absorber is resilient, not tough.
How to stop firefighting and start working proactively - George Sudarkoff
Tying nicely into the management garden discussion, Sudarkov talks about the problems caused by being in constant fire-fighting mode. He also alludes to one of the causes: it feels good and important to be putting out fires, and fire-extinguishing (since it’s so visible) can often be respected and rewarded in a way that running a quietly effective organization too often isn’t.
But fire fighting is exhausting, and it takes energy away from investing time and energy into growth and sustainable development.
Sudarkoff urges us to spend the time to stop fires from happening:
- If the fire-fighting is self-inflicted, fix the process problems [LJD: could also be a people problem] lighting the fires
- If the fire-fighting is externally inflicted, fix the (external) boundaries issues that leads to others causing fires for you.
Neither of those is necessarily easy to do, especially while your energies are still being taken up with conflagrations! But the alternative is to keep spending energy on firefighting.
Addressing Tech Debt - Abi Noda
Noda gives a nice overview of technical debt (along with a taxonomy of ten different kinds of technical debt). More importantly, I think, he talks about signs that the tech debt is causing problems. To my mind, the four most important factors are:
- Value lead time - it’s affecting how long it takes to do new things
- Impact to end user - it’s actually hurting the user experience
- Ability to onboard new developers
- Degradation of measures like infrastructure requirements, performance, availability
And when it does start to cause one of the above problems, he advises:
- Transparent information about the problems being caused
- Clear end-to-end ownership of code, so that:
- Empowered teams: the teams with ownership can include “debt repayment” in the work they’re doing, and
- Lightweight processes for monitoring improvement
Managing Your Own Career
If you are a native English speaker who uses Microsoft Teams for internal meetings, I highly recommend turning on Speaker Coach. That feature gives you a report after scheduled calls, flagging repeated or filler words (it turns out I say “you know”, “uh”, and “cool” a lot), talking too much during a meeting (something we managers need to look out for), flat speaking tone, and other speaking issues.
I can’t honestly say it’s been enjoyable to go through Speaker Coach reports, but it has been extremely valuable, and having those nudges and data after every meeting makes improving much easier.
Note that Speaker Coach currently only works in English, and I don’t know how well the word recognition functionality would work for people who have accents in English that come from speaking other languages too. (I imagine the flat speaking tone and speaking-too-much functionality would work, however)
Get straight to the point - James Stanier
Many of us were trained in academia, or have been in academic circles long enough to pick up some habits of thought.
That explicit or implicit academic training serves us well in a lot of ways! But not when it comes to communication.
The very stylized (and verbose…) form of communicating in scholarly journals and research presentations is an active hinderance when we’re trying to get things accomplished communicating with busy people.
I like tools like Hemmingway App to help me tighten up my text and make it more readable. But that can’t help with the structure or organization of what I write.
Stanier urges us to get straight to the point, with three clear recommendations:
- Make it clear up front what you want
- Make the next steps obvious
- If you already have a recommendation, say it
None of this has to come off as assertive or obnoxious - it’s just how you structure and order the information and request. It’s a matter of kindness to the reader - giving them what they need to provide an answer immediately (and get the email out of their inbox) if that’s possible.
When you’re not making a request but just communicating information, the Minto Pyramid is also a good approach.
Research Data Management and Analysis
GreptimeDB is Now Open Source - Xiaodan Zhuang, Greptime blog
Supporting and processing near-real-time data collection, especially from IoT sensors, is going to become a bigger piece of research computing and data. In many cases, ingesting and processing the data in large batches, as we’ve always done, will work just fine. But in others we’re going to need access to the data nearly as soon as it comes in, and some way of persisting it while analysis is being done. That’s going to require data solutions like time series databases.
Luckily, hyperscalers and even large enterprise deployments have been building time series databases for some time, to handle incoming telemetry data from huge numbers of servers and/or users.
Greptime looks to part of the next generation of solutions, taking lessons from time-tested approaches like InfluxDB. I’ll be keeping an eye on it.
Is anyone currently using time series databases in your work? Are there any gotchas you want other readers to know about, or solutions you’re really happy with? Let me know.
Research Computing Systems
Touching Grass With SLOs - Reid Savage
The Gordon Bell Special Award is always a nice glimpse into the future of research computing - this year’s winner involved training a 25 billion-element LLM diffusion model on huge stacks of data, fine tuning the model going through a subset of that data, running large molecular dynamics simulations, then running inference with another large model, OpenFold.
The hardware and software systems we are building to support these varied computational science studies with diverse interlocking computations are increasingly complex!
But our approach to thinking about “downtime” hasn't always kept up.
For most of RCD history, research computing systems were unambiguously up or down.
We’re already well past the point where that isn’t true any more - parallel file systems can be “up” but in a clearly degraded state, queueing systems can be borked with running jobs continuing along unaffected, etc.
The broken/working binary is going to get increasingly untenable as more and more systems support broader functionality. Functions as a service, database services, streaming data, workflow managers - these are increasingly key pieces of modern research computing workloads, and they can be up, down, working but with undesirably high latency or individual request failures…
Savage gives another nice of Service Level Objectives (SLOs: see also #44, #57, #73, #134). SLOs are targets for the health of pieces of functionality, defined - crucially - from the point of view of the user. These are internal targets, which are alerted on, and which may or not inform explicit, user-facing commitments (SLAs, service level agreements).
Our research communities deserve computing systems which are not merely “up” in some technical sense but useable. SLOs are a way of defining internal monitoring thresholds to better achieve that.
Does your team have SLOs? How did you decide what they'd be, and how has monitoring of them worked?
Emerging Technologies and Practices
In my day job I see a lot of teams who want to set up dynamic JupyterHub instances running reproducible workflows colocated with large data sets. NASA Openscapes is a cloud infrastructure for geospatial data, along with support for researchers migrating workflows to the cloud.
Lopez gives a quick overview of the 2i2c cloud infrastructure, with jupyterhub running on Kubernetes in a cloud-agnostic fashion, using GitHub for authentication as well as version control, a conda environment, and the ability to run across nodes with Dask.
I’m looking forward to there being standard, opinionated distributions of tooling to spin this kind of environment up from scratch; have you seen this kind of toolkit before? Do you run something like this? I’d love to hear about it.
The Journal of Fluid Mechanics will actively support supplementary materials in the form of runnable Jupyter Notebooks.
A computational biologist just won the Great British Bake-Off, for those who doubt the transferrable nature of RCD skills.
A lot of people are moving to Mastadon! I don’t have the bandwidth right now to be an early adopter, but if it pans out I might follow. If you’re thinking of hosting a Mastadon server, though, especially in the US, read this twitter thread on steps to take to protect yourself in the US from DCMA and other legal threats.
Why we call it boilerplate code.
Key chain fobs are ok, and apps for your phone are fine I guess, but wouldn’t you rather have your TOTP multi-factor authentication token generator running on a Commodore 64?
As you know, your loyal correspondent has a soft spot for embedded databases. Kùzu is a new embedded DB specifically for graph data.
Speaking of, SQL Teaching, an interactive SQL tutorial using sqlite in the browser.
Finding bugs in an alternate implementation of an algorithm without writing tests using property testing.
The flux framework is intended to be a next generation toolkit for building schedulers and resource managers for future HPC systems. In an attempt to provide a more converged HPC/cloud approach to jobs, a flux operator is being built to run on top of Kubernetes.
Technology investors are optimistic enough about the future of CXL “composable memory” approaches that companies like Astera are successfully raising money and increasing their valuation even during … all this.
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,
About This Newsletter
Research computing and data - 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 support 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 190 jobs is, as ever, available on the job board.
Software Development Manager - Quantum Software - Xanadu, Toronto ON CA
Xanadu is looking for an experienced Software Development Manager to lead the Core Quantum Software team. The team is developing PennyLane, an open-source framework for quantum machine learning, quantum computing, and quantum chemistry. Although quantum software development experience is not required for the role, an advanced degree in physics, math or computer science is preferred.
Technical Project Manager - Quantum Machine Learning - Qiamtomii, London UK
We are expanding the Machine Learning and Quantum Algorithms team with a Project Manager. In this role you will be responsible for supporting and managing technical client projects that apply quantum computing to use cases in machine learning, optimisation and simulation. This role is embedded in a team of applied scientists and researchers. The team focuses on making the most of today’s quantum computers with innovative quantum algorithms and a view towards early applications developed in collaboration with some of the largest global enterprises.
Lead Bioinformatician, NIHR BioResource - University of Cambridge, Cambridge UK
The NIHR BioResource is recruiting a Lead Bioinformatician to help us deliver our goals as one of the foremost contributors in the use of whole genome and RNA sequencing in the fight against rare diseases. As Lead Bioinformatician, you will be: - Managing the Bioinformatics team responsible for the delivery of timely, high-quality 'omics data both for research and potential novel diagnostic insight - Working with whole genome sequencing, RNA sequencing and proteomics data - Collaborating with other bioinformaticians and clinicians as they seek diagnoses for their patients - Overseeing the operations of the data ingest pipeline and managing its development to best meet the evolving needs of NIHR BioResource and its collaborators.
Senior Data Science Manager - Morgan Hunt (Recruiter), Glasgow UK
The postholder will be responsible for managing a team of data scientists, research engineers, and information professionals in support of the organisation's national data service and research centre activities as well as supporting related research activities. They will provide strategic leadership in data engineering, data science, research computing technology, and information governance for a centre which is pioneering developments in urban analytics and computational social science, and for developing, managing, and implementing research computing, data, and information services within the organisation.
Director, Data Science – Head of Impact Evaluation - Merck, Various NJ USA
The Director, Data Science (Head of Impact Evaluation) role will work within the Human Health Insights, Analytics and Data area to use advanced statistical methods and techniques to isolate the impact of data driven commercial interventions within Human Health. This will include measuring the impact of analytics that is currently to support the business (Next Best Action, Targeting lists, Prediction algorithms on HCPs and HCCs, etc.) and the impact of promotional work through methods like MMX. Their remit will be to help create feedback mechanisms for the work that is done in Human Health so that continuous improvement can occur, and the organization can mature towards a more agile way of thinking through a hypotheses driven and experimentation oriented mindset and culture.
Director, Data Science Partnerships - University of Miami, Coral Gables FL USA
The Director of Data Science Partnerships is responsible for seeking research engagement opportunities between IDSC faculty, complementary faculty, researchers, and industry to meet the objective of expanding the use of data science. The Director serves as a liaison to community leaders, external organizations, and stakeholders significant to the Institute for Data Science's strategic plans and initiates and manages programs that support the director’s vision for the Institute. The Director facilitates partnerships with universities, the corporate sector, NGOs, governments, international organizations including the Caribbean and Latin America and the like, in support of the Institute for Data Science and Computing’s basic and applied research initiatives
Geospatial Data Science and Applications Group Lead - Idaho National Laboratory, Idaho Falls ID USA or Remote USA
The Radiological Security and Mechanical Engineering Department at Idaho National Laboratory is seeking an eager, self-motivated, mid-career geospatial data scientist to be the managerial and technical lead for the Geospatial Data Science and Applications Group. Provide technical, strategic, and human capital leadership for the Geospatial Data Science and Applications Group. Oversee and leads the research, development, and deployment associated with operations research, dynamic systems modeling, and spatial analytics to fundamentally change how to analyze and extract knowledge, for complex system design and operations for energy and defense systems. Collaborate and partner with government agencies, academia, and private sector companies to achieve project objectives. Work with a multi-disciplinary team of scientists and engineers on challenging work scope and communicate effectively both verbally and in writing with management, co-workers, and with customers.
Quantum Information Science Program Manager - Berkeley Lab, Berkeley CA USA
Berkeley Lab (LBNL) is the home of world-class team science in service to the nation, and leads the Quantum Systems Accelerator (QSA), a 15-institution quantum information science (QIS) research center. Berkeley Lab’s Applied Math and Computational Research Division has an opening for a Quantum Information Science (QIS) Program Manager to support the QSA in achieving strategic program goals, maintaining relationships with high-level stakeholders in the academic, national laboratory, and industrial landscape, and managing the day-to-day operational aspects of scientific research and related quantum ecosystem activities.
Computational Cosmology Center Group Lead - Berkeley Lab, Berkeley CA USA
The Computational Cosmology Center (the C3 Group) is a team of astrophysicists, computational scientists, engineers, post-docs, and students with expertise in advanced computing techniques and their application to scientific collaborations, including cosmology and experimental and theoretical astrophysics. This position is for a Computer Staff Scientist as group lead of the C3 Group in the Computational Science Department in the Scientific Data Division. In this exciting role, you will conduct and lead computing research and/or development projects within or related to ongoing or future cosmology science collaborations including DESI, LSST-DESC, CMB-S4, Euclid, WFIRST among others.
Senior Lead Quantum Computing Engineer - Prudential, Newark NJ USA
Reporting to Global Technology’s Chief Architect, the Quantum Computing Senior Lead Software Engineer will evaluate, pilot, and evolve its approach to harnessing emerging Quantum Computing techniques, across its asset management and insurance capabilities. Responsibilities range from development of low-level Proof-of-concepts on existing quantum computing platforms under development in industry and academia, to more complex, cloud-based capabilities involving hybrid quantum-classical algorithms, run on quantum simulators and/or cloud platforms (e.g. AWS Braket). The ideal candidate is a full-stack developer with a DevOps mindset, with proficiency in both front-end and back-end development and has some background or experience in Quantum Computing.
Assistant Program Manager, Alternative Computing Paradigms (Quantum Information Science) - Johns Hopkins Applied Physics Laboratory, Laurel MD USA
We are seeking an Assistant Program Manager for Alternative Computing Paradigms (ACP), with a focus on quantum information science, within the Exploration Program Area of the Research and Exploratory Development (RED) Mission Area. In this role, you will jointly lead the ACP program and oversee a diverse, successful portfolio of pioneering research with established, expanding efforts in quantum information science (QIS), along with complementary fields (trustworthy computing, neurofidelic computing, and computational science). Work with the Program Manager to develop technical research strategy and outreach activities.
Manager, Research Informatics Data & Software Engineering - Weill Cornell College of Medicine, New York NY USA
Maintains software and data pipelines to support scientific workflows. Primary focus is on back-end and front-end application components, as well as the integration of data from multiple source systems. Through these activities, this role works with team members to provide robust, scalable software solutions to the research enterprise.
Director of Research Software Engineering - Cincinnati Children's Hospital, Cincinnati OH USA
Creates a vision and roadmap for the team that provides direction and alignment of priorities with the tactical and strategic objectives of the department and organization. Delegate responsibilities to reporting personnel, establish clear lines of responsibility and accountability. Elevates team members thinking and understanding of the field by infusing best practice knowledge into the work. Leads the selection, development, mentoring and coaching of direct and indirect reports. Ensure that job requirements and goals for each position are clear to employees and that Medical Center initiatives, priorities, standards, and policies are effectively communicated and understood.
Senior Manager, Data and AI Platforms - Seagen, Bothell WA USA
Seagen is a global, multi-product biotechnology company dedicated to developing and commercializing transformative cancer medicines. As the industry leader in antibody-drug conjugate (ADC) technology, we pioneered a new generation in the science of harnessing antibodies to deliver cell-killing agents directly to cancer cells. The Data Strategy, Science, & Solutions team’s (DSS&S) mission is to provide quality data, visualization, data science, & machine learning capabilities to enable Seagen to make impactful decisions, generate actionable insights, & create new patient value. The primary mission of the Sr. Manager of Data and AI Platforms is to lead the design, development, and execution of the Seagen Self-Service Data Platform in support of our mission to empower data teams across Seagen to deliver best-in-class data products.
Technical Lead, Machine Learning - Computer Vision - BenchSci, Toronto ON CA or Remote CA or USA or UK
We are looking for a Tech Lead to join our Machine Learning team. You're the perfect fit for this role if you are passionate about solving Computer Vision (CV) problems, have a great appreciation for science and want to transform how it is done. To be successful in this role, you will need to be comfortable leading the development of creative solutions while being results-oriented, honest and fast to act.
Senior / Principal Quantum Computing Scientist- Applications & Sales - PASQAL, Sherbrooke QC CA
PASQAL is opening a technical center in Canada which will provide quantum computing hardware capabilities and software services for North America. We are setting up a team of passionate people dedicated to promoting PASQAL's technology and educating the market on the power of neutral-atom quantum computing. As the SR/Principal RESEARCH SCIENTIST - QUANTUM ALGORITHMS, you will work among top-class engineers and scientists in the Quantum industry. You'll learn fast and naturally take the full dimension of the role, eventually becoming a key stakeholder of the quantum application software community in North America. You will work with the full-stack quantum team (developing application software and understanding hardware stakes). Being our first technical employee in CANADA, you will have a direct impact on the company.
Manager, Health Research Informatics, Cancer Digital Intelligence - University Health Network, Toronto ON CA
The Data Science team at Techna is looking for a dynamic Manager to join their team. The team works in close collaboration with care providers, researchers, and educators to develop innovative solutions that collect, manage, and leverage data to facilitate clinical research. Our systems are used in clinical practice and in multi-site research studies. The ideal candidate should have experience as a product manager in health sciences and bioinformatics. This role requires experience in using a range of different technologies and frameworks to create innovative healthcare solutions. You will work on novel health technologies that will help accelerate cancer research, including health data interoperability platforms and integrated predictive models.
Program Manager (McGill University Health Centre Research Institute) - McGill University, Montreal QC CA
Under the general supervision of the Director of the DREAM-CV lab, the employee’s goal is to assist with and secure research funding. The incumbent is responsible for drafting grant proposals, papers which includes but is not limited to preparing, reviewing, editing, budgeting, and managing and submitting proposals according to established methods. In addition, the incumbent supports the scientific aspect of the Program, directly involved in several cardiology research projects and supervision of Master and PhD students. Lead scientific studies within the lab
Manager, Artificial Intelligence Policy - GSK, London UK
At GSK, we are using Artificial Intelligence (AI) and Machine Learning (ML) to develop new therapies and personalized drugs that drive better outcomes for patients. Because the datasets we use and algorithms we build at certain steps of the drug development journey have ethical and safety implications for our patients, GSK has a dedicated team working on the responsible use of AI in healthcare. To help inform these efforts, GSK sponsors AI Ethics and Safety Fellows at Stanford University and the University of Adelaide, as well as actively pursuing applied ethics and safety research projects within the company.
Cancer Clinical Informatics Lead - University of Cambridge, Cambridge UK
The CRUK Cambridge Cancer Centre is looking for an experienced Cancer Clinical Informatics Lead to develop a team to design and build infrastructure and supply data to meet the varied needs of our many researchers. Our data includes clinical records, genomics, imaging, research assays and continually evolves as our research grows. Working with senior clinicians and laboratory scientists, our NHS partners and industry collaborators, the successful candidate will develop a strategically important data infrastructure that allows our researchers to harness this wealth of electronic data for ultimate patient benefit.
Translational Research Manager (Artificial Intelligence) - University of Manchester, Manchester UK
The University of Manchester is seeking to appoint an individual with a track record of building and leading collaborative relationships and professional networks, expertise in a domain ideally related to artificial intelligence, excellent communication and interpersonal skills, and experience in managing high-performing teams, to take up the role of Translational Research Manager for AI.
Senior Manager/Director of Data Science - Genescopy, Remote USA
Position Summary: The Senior Manager/Director of Data Science leads the Data Science Team while collaborating with Research and Development (R&D), Engineering, Clinical, and Product Development personnel to build analytics and computing infrastructures for new and innovative diagnostic tests. Leads the Data Science Team, a research team of data scientists and bioinformatics engineers. Leads data science development, contributes to problem-solving, and collaborates internally and externally on various research projects. Designs and implements solutions to extract and validate signals from complex genetic and genomic data.
AI/ML Senior Lead Research Scientist - L4Harris, Tulsa OK or Mason OH USA
L3Harris Aeromet has an opportunity for an Image Science Engineer working to enhance and develop image processing techniques for our advanced EO/IR mission systems. The selected engineer will be a key member of a team applying AIML techniques to real world applications to close gaps that are critical to mission success for service members in the field. Technologies you develop will consistently provide faster decision-making capabilities and increase the utilization and productivity of its users.
Project Manager, Biomedical Informatics - University of Pittsburgh, Pittsburgh PA USA
This Project Manager position at the Department of Biomedical Informatics is responsible for the coordination and support of SenNet and other Common Fund and related programs in the funded ecosystem. The candidate will be a point of contact with funding agencies and partnering institutions for administrative and technical issues. Responsibilities include day-to-day management of project activities, managing all project-related meetings and communication with external institutions, developing schedules and milestones for internal team and for collaborative efforts with other teams, and meeting those schedules. Responsible for coordinating the teams’ efforts to develop and benefit from inter-institutional programs. This position will be responsible for producing and maintaining all administrative and substantive reports and presentations.
Managing Director, Research Technologies - Harvard Buisness School, Boston MA USA
Reporting to the Chief Information Officer, Harvard Business School (HBS) you will lead a vibrant group of technologists and multimedia specialists who work closely with HBS faculty to develop products based on their research, while also developing a research computing support practice that meets HBS’s evolving needs in that arena. As the leader of the Research Technologies department, you will partner with faculty, research assistants, and administrators to focus on the discovery, development, and delivery of technology supported methods to enhance research, teaching, and learning effectiveness. You will work collaboratively across the campus leveraging activities and opportunities with/across the Division for Faculty and Research Development (DRFD), Baker Library, Harvard Business School Publishing (HBP), and Harvard University IT (HUIT). You must be able to build strong community-wide relationships and be viewed as a trusted partner who is an expert in the field of research technology.
Research Data Support Manager, Library Services - St. George's University of London, London UK
St George’s is a world-leading healthcare research University, and many of our translational programmes and projects benefit from research data management. We are seeking an enthusiastic, experienced individual to lead and deliver our already established research data management service which includes the storage, preservation, and discoverability of the Institution’s research data assets. You will have either a background in research (as a programme manager, or involvement in research projects) or in open science (for example as part of a library or research office team).
Digital Technology Infrastructure Manager - Raytheon, East Hartford CT USA
The Raytheon Technologies Researcher Center (RTRC) Infrastructure manager, will manage all aspects of the DT infrastructure at RTRC. This management will include oversight of third-party sysadmins, hardware obsolescence planning, software installation and patching. In addition, this role will work cooperatively with the Sr. Manger of RTRC Linux/HPC and the on-premises HPC infrastructure needs. This person must also be willing to get hands-on as needed. The candidate will report to the Sr. Manager of Digital Technology, RTRC.
Systems/IT Architect Principal, Partnership for Advanced Computing Environment - Georgia Tech, Atlanta GA USA
Under minimal guidance, provide advanced level support services to units or on campus wide basis involving conceptualizing, planning, designing and implementing complete and integrated information technology solutions that meet business needs and support long term goals. May provide leadership to technical teams or functional programs.This position will interact on a consistent basis with: User department managers and staff, IT management and professional staff, vendors and contractors. This position typically will advise and counsel: User department managers and staff, IT professional staff, vendors and contractors. This position will supervise: NA (work direction only).
Senior IT/Computing Architect, Einstein Telescope - University of Geneva, Geneva CH
The Department of Astronomy and the Gravitational-Wave Science Center (GWSC) at the University of Geneva is looking for a Senior Information Technology (IT) to support the activities of the Einstein Telescope (ET) project in the design of the computing model and infrastructure of the next-generation gravitational-wave observatory. The successful candidate will work within one of the ET-PP work packages towards the definition of the requirements and architecture of the computing model for the Einstein Telescope project, including all stages of data acquisition, processing and analysis. Review and evaluate the computing model of current generation gravitational-wave observatories and other similar-scale experiments and observatories in physics, astronomy, and related domains. Take a leading role in establishing a close collaboration with domain experts from the ET.
Bioinformatic Research Scientist/Lead-Bioinformatics Analyst - St. Jude Children's Hospital, Memphis TN USA
The Northcott Lab in the Department of Developmental Neurobiology at St. Jude Children’s Research Hospital is seeking a highly motivated Lead Bioinformatics Analyst/Bioinformatics Research Scientist to lead multi-omics studies dissecting molecular heterogeneity underlying the pathogenesis of childhood brain tumors. The Northcott Lab is internationally renowned for its expertise in the genomic analysis of pediatric brain tumors, with a track record substantiated by transformative publications in top-tier journals such as Nature, Cancer Cell, Lancet Oncology, Journal of Clinical Oncology, and more. In this position, the candidate will lead cutting-edge computational analyses of multi-omics datasets derived from large patient cohorts.
Manager, Learning Solutions - DWave, Remote USA
The Manager of Learning Solutions will be responsible for the design, preparation, delivery, and needs assessment for product and process-focused training programs for D-Wave customers and partners. This individual will be fluent with the lifecycle of learning design and have tactical experience building measurable learning experiences and programs across a spectrum of curricula (product, systems, technical, and functional knowledge). In addition, this individual will be responsible for determining the methods for evaluation and effectiveness of training courses as well as ongoing excellence in exceeding those goals.
Lead Scientist Quantum Computing - Honda Research Institute, San Jose CA USA
As a Lead Scientist, you will lead the investigation of quantum computing to a challenging area of intelligent systems. You should grow into the role of an ambassador for QC in our company. This position requires research and leadership skills, solid knowledge in computer science and areas of mathematics related to quantum computing. Previous experience in developing and deploying quantum computing software in hybrid or standalone context are a big plus.
Director of Data Engineering - Commonwealth of Massachusetts, Boston MA USA
The Executive Office of Technology Services and Security (EOTSS) is seeking an experienced Director of Data Engineering to join our Data Office. As part of the Commonwealth’s central data team, you’ll be on the front lines working to improve the value of our data systems across state government. As Director of Data Engineering, you will lead the team’s data engineering efforts develop and maintain smart, secure data systems and pipelines, while building capacity for innovation in government.