Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Harvard University
- Technical University of Denmark
- King Abdullah University of Science and Technology
- NIST
- Xi'an Jiaotong - Liverpool University
- AALTO UNIVERSITY
- Aalborg University
- ETH Zurich
- Helmholtz Association of German Research Centres
- Luxembourg Institute of Science and Technology (LIST)
- National Aeronautics and Space Administration (NASA)
- Pennsylvania State University
- Sandia National Laboratories
- Technische Universität Dresden (TU Dresden)
- UNIVERSITY OF HELSINKI
- University of Kansas Medical Center
- University of Oslo
- University of Tennessee at Chattanooga
- University of Wisconsin Madison
- Utrecht University
- 10 more »
- « less
-
Field
-
Department: SOM KC Cancer Biology ----- Bossmann Position Title: Cancer Biology/PISR Post Doctoral Fellow Job Family Group: Professional Staff Job Description Summary: The postdoctoral fellow will
-
mathematics and scientific computing? Are you passionate about impacting problems of national importance? If so, envision the opportunities as Sandia's next John von Neumann Postdoctoral Fellow. We
-
under uncertainty and contribute approaches that can be transferred to deltas worldwide. Your qualities We are looking for an enthusiastic and collaborative postdoctoral researcher with a strong
-
to add the job to your shortlist Get job alerts Create a job alert and receive personalised job recommendations straight to your inbox. Create alert Similar jobs ACER CoE - Postdoctoral Researcher in
-
and receive personalised job recommendations straight to your inbox. Create alert Similar jobs Research Fellow in Remote Sensing and AI Cranfield, United Kingdom COLCOM - Postdoctoral Researcher in Multimodal Crop Analysis & Fertilizer Optimization Benguerir, Morocco (MA)
-
Job Description We are seeking 1-2 highly motivated and talented postdoctoral researchers to join our team at DTU Physics and contribute to ScaleQ, a new project on scalable photonic quantum
-
. Artificial Intelligence: proven ability to design and deploy AI/ML solutions on heterogeneous urban data (spatio-temporal modelling, forecasting, computer vision, optimization, generative and agentic
-
probabilistic behavioral models for model checking, performance evaluation, and optimization. The overall objective is to establish formal foundations that bridge static engineering descriptions and
-
; while they are trained using GPU-based optimization methods, the actual information processing takes place without a GPU, making them energy-efficient and fast. Diffractive networks are to be designed