Research Computing Teams Micro-roundup, 11 June 2021
Hi, everyone!
Mainly taking the week off from the newsletter this week (for positive reasons - some family celebrations); things will return to normal next week. But there were some things I wanted to share with you.
First, on the discussion from last week of planning for hybrid distributed/local work, we heard from long-time reader Adam DeConinck about what he's learned:
I’m fortunate at the moment, because my current team was fully remote before the pandemic started. That said, here are a few thoughts based on some of my recent experience.
Several of my past roles have already been “hybrid”, where either some employees were remote vs some not; or where employees were split across many offices in multiple time zones, which often led to similar communication challenges.
The general philosophy that has seemed to work has been to split “location” by team. I.e., everyone on a team should either be remote, or should be co-located in the same office. This basically works to allow each team to find their rhythm.
In the cases where teams have been split across different work “locations”, I’ve mostly seen the effective formation of “sub-teams”. E.g., while the [city X] and [city Y] offices may in theory both have members on the same team, they tend to split responsibilities to minimize overlap. Or, if there’s a core group in the office but a few remote folks, the remote team members form their own “team” where they mostly collaborate with each other.
Based on this experience, I suspect organizations which are large enough to have a lot of teams will go through substantial re-orgs over the next year!
Granted, this is a lot harder for orgs where there are fewer teams, or where they’re smaller or harder to split. In those cases, unless everyone can make it back into the office, I think the only thing that works is to go the “remote first” model: everyone works as if they were remote, joining video calls individually and putting most communication in text. And then in-office interaction is purely social.
This is really valuable; thanks, Adam!
On the other hand, I also heard from readers whose institutions are decidedly not moving to hybrid or remote work but instead expect everyone back as soon as possible. In a way that's a lot easier, but it certainly ties a hiring managers hands behind their backs in recruiting new hires, or retaining those who have come to like not having to commute every day.
If your team manages systems, you've probably heard about the really pretty bad privilege-escalating polkit vulnerability that affects RHEL8, Fedora 21+, Debian testing, and Ubuntu 20.04 If you haven't, you'll want to update (a fix was released last week). The post is a really detailed overview of the bug and the proof of concept exploit.
Titus Brown generously shared the core of a Chan Zuckerberg Initiative (CZI) Essential Open Source Software for Science grant application in a blog post which you can read here; the proposal aims to make their package sourmash more of a community code by moving towards more community engagement.
The post is interesting both if you're interested in CZI grants but also to see how a PI quite experienced in research software development thinks about building community engagement.
As a side note I'd love to see more research computing and data grant proposals being made public!
There's a call for papers due on Monday, 14 June, for a workshop on Resilience in HPC Clusters, Clouds, and Grids; the workshop is held in conjunction with Euro-Par 2021, to be held on-site in Lisbon.
And that's it for this mini-roundup. Please keep feedback coming in, and welcome to all new readers.
Have a great weekend, and good luck in the coming week with your research computing team!
Jonathan
Jobs Leading Research Computing Teams
This week’s new-listing highlights are below; the full listing of 174 jobs is, as ever, available on the job board.
Senior Bioinformatics Specialist - Rutgers Cancer Institute of New Jersey, New Brunswick NJ USA
The primary purpose of the Senior Bioinformatics Specialist is to work closely with the CIO and other members of the team to ensure the success of the Biomedical Informatics mission: realizing translational medicine by working at the interface of IT, biology, and medicine to link bench and bedside using chemical informatics software technologies. The Bioinformatics Specialist will support the computational biology and cheminformatics needs of researchers at the Rutgers Cancer Institute of New Jersey.
Director, Biostatistics, Oncology Safety Group Lead - Daiichi Sankyo, Basking Ridge NJ USA
Serves as project statistician and ensures the study designs are scientifically sound, the efficacy and safety information meet regulatory requirements of the countries and Regions the drugs will be submitted. Ensures consistency in data collection, derived data definition, analysis file structure, statistical analysis and result interpretation throughout the drug project; Leads the planning and analysis of integrated efficacy and safety data; Review the relevant sections of the electronic common technical document (eCTD).
Manager, Statistical Programming - Translational Medicine - Daiichi-Sankyo, Basking Ridge NJ USA
By leading internal programming contractor or by self, perform programmatic review of analysis datasets and TLFs generated by statistical vendor, ensure deliverable quality for the pivotal studies, Integrated Summary of Efficacy (ISE)/Integrated Summary of Safety (ISS) for oncology submission compounds, and expedite the preparation of regulatory submissions. Responsibilities include: review Case Report Form (CRF) annotation and Study Date Tabulation Model (SDTM) dataset, identify data inconsistencies and support data review, review analysis dataset specifications and ensure correct interpretation of SAP, develop independent programs to validate analysis dataset and TLFs generated by vendor, ensure analysis dataset in compliance with CDISC and submission requirement, review submission data package and ensure its quality and integrity.
Senior Product Manager - Data Science - Veeva, Toronto ON CA or Pleasanton CA USA
Own and design data focused product features start to finish, including user stories, specifications, quality control checks, and data dictionaries
Collaborate with Data Scientists to find meaning in high volumes of data using statistical analysis in an approach that can be productized at scale
Author high-quality design specifications within an agile methodology
Product Manager - VFX & Animation Algorithms - Netflix, Los Gatos CA USA
You will be part of the Algorithms Product Management team; a diverse and unique group of leaders drawing on a variety of backgrounds to connect cutting edge machine learning to great member experiences and business value. We lead algorithm-centered innovation projects but also partner across the company to enable better data-driven solutions to a variety of business problems. The Algorithms PMs influence, educate, and advocate on tactical product decisions as well as the strategic directions to enable the next slate of great product innovations.
SAS Data Engineering Manager - Accenture, Montreal QC or Toronto or Ottawa ON CA
As a SAS Engineer, you are passionate about data and technology solutions, are driven to learn about them and keep up with market evolution. You will play an active role throughout the entire engagement cycle, specializing in modern data solutions including designing and delivering performant Business Intelligence SAS applications to our clients by supporting our engagement teams in collaboration with the project manager. You are enthusiastic about all things data, statistics, data mining, customer intelligence and advanced analytics. If you have strong problem-solving and analytical skills, are tech savvy and have a solid understanding of software development, then this role may be for you.