Connectionists: job post: machine learning research scientist at NIMH

[Francisco Pereira]

### HIRING: machine learning research scientist

The Machine Learning Team at the National Institute of Mental Health (NIMH)
in Bethesda, MD, has an open position for a machine learning research
scientist. The NIMH is the leading federal agency for research on mental
disorders and neuroscience, and part of the National Institutes of Health
(NIH).

### About the NIMH Machine Learning Team

Our mission is to help NIMH scientists use machine learning methods to
address a diverse set of research problems in clinical and cognitive
psychology and neuroscience. These range from identifying biomarkers for
aiding diagnoses to creating and testing models of mental processes in
healthy subjects. Our overarching goal is to use machine learning to
improve every aspect of the scientific effort.

We work with many different data types, including very large brain imaging
datasets from various imaging modalities, behavioral data, and picture and
text corpora. We have excellent computational resources, both of our own
(tens of high-end GPUs for deep learning, several large servers) and shared
within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds
of GPUs).

As a machine learning research group, we develop new methods and publish in
the main machine learning conferences (e.g. NeurIPS and ICLR), as well as
in psychology and neuroscience journals. Many of our problems require
devising research approaches that combine imaging and non-imaging data, and
leveraging structured knowledge resources (databases, scientific
literature, etc) to generate explanations and hypotheses. You can find more
about our work and publications at

https://cmn.nimh.nih.gov/mlt

### About the position

We are seeking candidates who are capable of combining machine learning,
statistical, and domain-specific computational tools to solve practical
data analysis challenges (e.g. designing experiments, generating and
testing statistical hypotheses, training and interpreting predictive
models, and developing novel models and methods). Additionally, candidates
should be capable of visualizing and communicating findings to a broad
scientific audience, as well as explaining the details of relevant methods
to researchers in a variety of domains.

Desirable experience that is not required, but will be considered very
favorably:
- neuroimaging data processing and analysis (any MRI modality, as well as
MEG and EEG)
- other types of neural data (e.g. neural recording, calcium imaging)
- modelling of human and animal learning and decision-making
- Bayesian statistical modelling

Finally, you should have demonstrable experience programming in languages
currently used in data-intensive, scientific computing, such as Python,
MATLAB or R. Experience with handling large datasets in high performance
computing settings is also very valuable. Although this position requires a
Ph.D. in a STEM discipline, we will consider applicants from a variety of
backgrounds, as their research experience is the most important factor.

This is an ideal position for someone who wants to establish a research
career in method development and applications driven by scientific and
clinical needs. Given our access to a variety of collaborators and large or
unique datasets, there is ample opportunity to match research interests
with novel research problems. We also maintain collaborations outside of
the NIH, driven by our own research interests.

If you would like to be considered for this position, please send
francisco.pereira at nih.gov a CV, with your email serving as cover letter. We
especially encourage applications from women and members of
underrepresented groups. If you already have a research statement, please
feel free to send that as well. There is no need for reference letters at
this stage. Other inquiries are also welcome. Thank you for your attention
and interest!
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