34 parallel-computing "LA TROBE UNIVERSITY" Fellowship positions at Indiana University
Sort by
Refine Your Search
-
Posting Details Position Details Title Institute for the Study of Contemporary Antisemitism (ISCA) / Borns Jewish Studies Program - Visiting Research Fellow Appointment Status Non-Tenure Track
-
Summary Center for Possible Minds Postdoctoral Fellow Vacancy The Center for Possible Minds at Indiana University, Bloomington, invites applications for Postdoctoral Fellows to join its Program for Advanced
-
, omics, physiological signals, clinical notes), and causal AI (causal inference, discovery, counterfactual reasoning). The successful candidate will collaborate with an interdisciplinary team of computer
-
Position Summary Dr. Matthew Aalsma, Vice Chair of Health Services Research and Director of the Adolescent Behavioral Health Research Program in the Department of Pediatrics at Indiana University School
-
Specialist for a National Institutes of Health (NIH) funded fellowship in public and population health informatics. This unique post-doctoral program is located on Indiana University’s Indianapolis campus
-
epidemiology using mathematical, computational, and statistical modeling. We are seeking researchers who are passionate about understanding the mechanisms driving epidemic spread, designing mathematical models
-
bioinformatics and biomarker research. This position focuses on the integration and analysis of complex biological data to identify and validate kidney disease biomarkers. Research Focus Our program leverages
-
Position Summary Dr. Matthew Aalsma, Vice Chair of Health Services Research and Director of the Adolescent Behavioral Health Research Program in the Department of Pediatrics at Indiana University School
-
Biomedical Engineering & Informatics, and Associate Director for AI Research at the Center for Computational Biology and Bioinformatics. Dr. Duren’s research focuses on development of computational methods and
-
: (1) Designing, implementing, and overseeing research projects focused on methods development for understanding genetic variation within and between populations, (2) building computational pipelines