See also:
- Staff Scientist Position in the Scientific and Statistical Computing Core (AFNI group)
- Postdoctoral position in functional imaging methods (Peter Bandettini Lab)
- Machine Learning Scientist Position (Francisco Pereira group)
- Computational Program Officers in NIMH
- Chief Data Strategist for NIH
The National Institute of Mental Health (NIMH) is the largest funder of research on mental disorders in the world, with a current budget of over $1.4B. Our mission is to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery, and cure. The NIH is a highly rated employer at glassdoor.com with very competitive salary and benefits packages.
The Data Science and Sharing Team (DSST) is a new group created to develop and support data sharing and other data-intensive scientific projects within the NIMH Intramural Research Program (IRP). Working closely with the NIH Data Science Community the goal of the DSST is to make the NIMH IRP a leader in open science and data sharing practices. We are looking for a talented Data Scientist to add to our team. Typical compensation for NIH staff scientists is available at Glassdoor.
You will work with a team of researchers and developers to build and deploy neuroimaging data processing pipelines for investigators within the NIMH IRP. You will collaborate with and contribute to other projects throughout the world that are building standards and tools for open and reproducible neuroscience (e.g. NiPy, BIDS, Jupyter, etc). You'll have the resources of the NIH HPC Cluster at your disposal as well as additional help from the AWS cloud. Everything we make is open source and freely distributed.
You will work to bolster data science skills within the NIMH IRP by teaching courses to scientists on best data practices (e.g.Data Carpentry and ReproNim) as well as interfacing with specific neuroimaging repositories (e.g. The Human Connectome Project, OpenfMRI, UK Biobank,The NIMH Data Archive).
Our team is committed to the NIMH Mission of understanding and treating mental illness and we believe open, clean data (and lots of it) is crucial to realizing that mission. You will work closely with (and sit next to) the Machine Learning Team who are building the models needed to understand complex brain function.
You should be comfortable with building processing pipelines for biomedical imaging data (e.g. fMRI, calcium imaging, electrophysiology, etc). You should also have experience coding in modern languages currently used in data-intensive, scientific computing such as Python or R. Alternatively, you may be more proficient in front-end development and visualization with Javascript. Experience with distributed, high-performance computing tools such as Docker/Singularity and batch processing systems such as SLURM is a plus.
Ideally we would like to see a recent degree (BS, MS, or PhD) in a STEM field, but if you can prove you have an equivalent amount of expertise with your publications, projects, or github/kaggle ranking, we’re all ears. We are also interviewing students and part-time staff if you’re still working on your degree.
We're looking for someone who's motivated to develop and research their own ideas. You should be willing and able to argue for the priorities you think the team should focus on, and work together to achieve those goals. You should be a self-learner and a self-starter. Please provide some examples of things you have worked on independently.
Email your resume, a cover letter, and a code sample that demonstrates you are all three of the above to:
DATASCI-JOBSEARCH@mail.nih.gov
The National Institutes of Health is an equal opportunity employer. This position will be based at NIMH in Bethesda, MD via a third party contracting firm.