84 big-data-and-machine-learning-phd "https:" Postdoctoral research jobs in United States
Sort by
Refine Your Search
-
Listed
-
Employer
- New York University
- Stanford University
- University of North Carolina at Chapel Hill
- University of Washington
- Cornell University
- Brookhaven National Laboratory
- Nature Careers
- Oak Ridge National Laboratory
- Princeton University
- Argonne
- Arizona State University
- Brown University
- Michigan State University
- National Renewable Energy Laboratory NREL
- Texas A&M University
- University of Colorado
- University of Florida
- University of Nevada, Reno
- University of South Carolina
- Argonne National Laboratory
- Boston University
- Duke University
- East Carolina University
- Harvard University
- Massachusetts Institute of Technology (MIT)
- Northeastern University
- Rutgers University
- Texas Christian University
- The University of Iowa
- University of California
- University of Connecticut
- University of Houston
- University of Minnesota
- University of Nevada Las Vegas
- University of Texas at Arlington
- University of Texas at Dallas
- Vanderbilt University
- Washington University in St. Louis
- 28 more »
- « less
-
Field
-
to contribute to one or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer
-
machine learning models. Working with extremely large, multi-modal datasets. Prior experience in analysis of clinical health records, and time series data are highly preferred. Qualifications Requirements
-
research, machine learning or artificial intelligence (e.g., large language models, EHR foundation models), causal inference (e.g., target trial emulation), and child health research. The research program
-
and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
-
resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
-
Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
-
reconstruction and tracking performance evaluation Knowledge and programming experience in scientific Machine Learning Working knowledge of large-scale data processing Programming experience in C++, ROOT, and
-
applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
-
systems, large multimodal foundation model training and/or finetuning, and continuous learning pipelines. Experience in multi-modality data analysis (e.g., image, video, text). Experience working in
-
as a one‐year appointment, but renewable annually based on performance. The position involves postdoctoral work in developing efficient methods and tools for analyzing large-scale biomedical data with