Data ScientistApplications Closed
Francisco Pereira
Bethesda, Maryland, United States of America
Apply by Jun 1, 2022
Application deadline
Jun 1, 2022
Job
Job location
Francisco Pereira
Bethesda, Maryland, United States of America
Geocoding in progress.
Source: legacy
Quick Information
Application Deadline
Jun 1, 2022
Start Date
Flexible
Education Required
See description
Experience Level
Not specified
Job
Job location
Francisco Pereira
Job Description
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).
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, from helping discover or develop theories to generating actionable results.
For more information, please refer to the full ad
https://nih-fmrif.github.io/ml/index.html
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, from helping discover or develop theories to generating actionable results.
For more information, please refer to the full ad
https://nih-fmrif.github.io/ml/index.html
Requirements
- 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:
- deep learning
- reinforcement learning
- Bayesian statistical modelling
- other types of modelling of human/animal learning and decision-making
- neuroimaging data processing/ analysis (any MRI modality
- MEG
- or EEG)
- other types of neural data (e.g. neural recording
- calcium imaging)
- in the context of substantial research projects
- ideally having led to submitted or published articles.
- 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. Backgrounds of team members include computer science
- statistics
- mathematics
- and biomedical engineering.
Job
Job location
Francisco Pereira
Coordinates pending.