The BRAIN Initiative seeks a data scientist to join its team to solve knowledge integration challenges and develop the BRAIN initiative Workspace to ORganize the Knowledge Space (BRAIN WORKS) platform.
The Scholar will serve a critical role in working with brain circuit research teams to curate theories and models of the brain into existing knowledge extraction platforms to address the following knowledge integration challenges:
- Model integration: to link theoretical constructs, model parameters, and model uncertainty.
- Data integration: to link heterogeneous data and disparate knowledge.
- Data imputation: to address data sparsity and uncertainty.
- Model simulation and data visualization: to unveil the hidden rules governing dynamical systems.
- interpret scientific knowledge and expose assumptions in existing model code and documentation.
- identify new data and information resources automatically.
- extract and integrate useful information into machine-curated expert models.
- execute models in robust ways.
The Scholar will apply the latest AI methods to neuroscience models and data to potentially change the legacy of the BRAIN initiative.
- data from BRAIN-funded projects examining brain circuits at various spatial and temporal scales, in a variety of species, under unique mental and behavioral paradigms, using multiple theoretical constructs to build testable hypotheses.
- a variety of models and data from literature describing high-resolution, large-scale, multi-modal, multiscale recordings of neuronal activity collected during complex behaviors and/or causal manipulations.
Applicants should possess technical skills in one or more of the following areas, as relevant to their proposed project area(s): artificial intelligence, cloud computing, data engineering, data science, database management, project management, software design, supercomputing, and/or bioinformatics. Industry experience is desired. Applicants should have an M.D., Ph.D. or equivalent doctoral degree and have advanced experience in data science or related fields. Appointees may be U.S. citizens, resident aliens, or non-resident aliens with, or eligible to obtain, a valid employment-authorization visa.
- understanding of data science, computer science, systems engineering theory, control systems theory, signal and information
- theory, mathematics, and statistics.
knowledgeable in mechanistic, multiscale modeling of dynamical systems.
- ability to communicate with niche audiences (neuroscientists with various backgrounds)
- ability to initiate and implement new ideas.
familiarity with one or more of the following programming languages and computing platforms: R, Python, TensorFlow, Jupyter Notebook).
Please see instructions here: datascience.nih.gov/data-scholars
This post will be available until June 20, 2020.
DHHS and NIH are Equal Opportunity Employers. Applications from women, minorities, and persons with disabilities are strongly encouraged.
The National Institutes of Health is made up of 27 different components called Institutes and Centers. Each has its own specific research agenda, often focusing on particular diseases or body systems. All but three of these components receive their funding directly from Congress, and administrate their own budgets. NIH leadership plays an active role in shaping the agency’s research planning, activities, and outlook. The Office of the Director is the central office, responsible for setting policy for NIH and for planning, managing, and coordinating the programs and activities of all the NIH components.
About NIH Office of Intramural Training & Education (OITE)
The NIH Office of Intramural Training & Education (OITE) is a division of the Office of Intramural Research (OIR), Office of the Director (OD). Our mission is to enhance the training experience of students and fellows on all of the NIH campuses. We work closely with the Training Offices in the NIH Institutes and Centers to help trainees in the Intramural Research Program (IRP). The intramural program is the sum of all the research projects carried out by NIH investigators and trainees in NIH facilities) develop scientific and professional skills that will enable them to become leaders in the biomedical research community.