Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- Johns Hopkins University
- Harvard University
- UiT The Arctic University of Norway
- University of Texas at Austin
- Nature Careers
- King's College London
- University of Michigan
- NTNU Norwegian University of Science and Technology
- University of North Carolina at Charlotte
- University of Texas Rio Grande Valley
- Université Gustave Eiffel
- Zintellect
- Aarhus University
- AbbVie
- Amgen
- Auburn University
- Barcelona Beta Brain Research Center
- Beijing Institute of Technology
- Carleton University
- Dana-Farber Cancer Institute
- Duke University
- Hong Kong University of Science and Technology
- Indiana University
- Institute of Computer Science CAS
- London Institute for Mathematical Sciences
- Northeastern University
- UNIVERSITY OF VIENNA
- University College London
- University of California, San Diego
- University of Denver
- University of Graz
- University of Idaho
- University of Illinois at Springfield
- University of North Carolina at Chapel Hill
- University of Nottingham
- University of Rhode Island
- University of Stavanger
- University of Utah
- University of Vienna
- Università degli Studi di Napoli Federico II
- Xi'an Jiaotong - Liverpool University
- Łukasiewicz PORT
- 33 more »
- « less
-
Field
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 hour ago
for data management and statistical analyses • Strong intellectual curiosity and ability to work independently within a collaborative, interdisciplinary team • Attention to detail Departmental Preferred
-
Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
-
. Interdisciplinary Research: This position is two- or three-year research endeavor to support postdocs whose innovative projects in cybersecurity will be able to integrate domain-knowledge of cyber physical
-
communication systems. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on