Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Stanford University
- University of North Carolina at Chapel Hill
- University of Minnesota
- NEW YORK UNIVERSITY ABU DHABI
- UNIVERSITY OF VIENNA
- CNRS
- Cornell University
- EPFL
- New York University
- Northeastern University
- Chalmers University of Technology
- Delft University of Technology (TU Delft)
- FAPESP - São Paulo Research Foundation
- KTH Royal Institute of Technology
- SciLifeLab
- THE UNIVERSITY OF HONG KONG
- The University of Iowa
- University College Cork
- University of Florida
- University of Texas at Arlington
- Utrecht University
- AALTO UNIVERSITY
- Aalborg University
- Aarhus University
- Baylor University
- European Space Agency
- Forschungszentrum Jülich
- Inria, the French national research institute for the digital sciences
- Istituto Italiano di Tecnologia
- Maastricht University (UM)
- Massachusetts Institute of Technology
- Pennsylvania State University
- UNIVERSIDAD POLITECNICA DE MADRID
- UNIVERSITY OF HELSINKI
- University of Washington
- Yale University
- ;
- AWI - Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Austrian Academy of Sciences, The Marietta Blau Instiute (MBI)
- Broad Institute of MIT and Harvard
- CEA
- Computer Vision Center
- Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke
- ETH Zürich
- East Carolina University
- Empa
- Fundació per a la Universitat Oberta de Catalunya
- Heidelberg University
- Högskolan i Skövde
- INSERM
- IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences)
- Indiana University
- Institut Pasteur
- Institute for bioengineering of Catalonia, IBEC
- KU LEUVEN
- Lancaster University
- Lunds universitet
- Missouri University of Science and Technology
- National Aeronautics and Space Administration (NASA)
- Radboud University Medical Center (Radboudumc)
- Research Center for Molecular Medicine (CeMM), ÖAW
- Saarland University
- The Ohio State University
- The University of Arizona
- Tsinghua University
- Télécom Paris
- U.S. Department of Energy (DOE)
- Umeå University
- University College Dublin
- University of California Berkeley
- University of California Irvine
- University of Canterbury
- University of Illinois at Chicago
- University of Liège
- University of Massachusetts Chan Medical School
- University of South Carolina
- University of Southern California
- University of Tasmania
- University of Turku
- University of Vienna
- University of Warsaw
- Universität für Bodenkultur
- Université de Caen Normandie
- Vrije Universiteit Amsterdam (VU)
- Washington University in St. Louis
- Westlake University
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- 78 more »
- « less
-
Field
-
. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
-
for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI
-
of 3D data / point clouds. Knowledge of libraries or tools such as PCL, Open3D, PDAL, and CloudCompare, as wellas machine learning/deep learning methods applied to 3D data, will be considered an asset
-
/ Population-scale multiome immune cell atlas reveals complex disease drivers https://www.medrxiv.org/content/10.1101/2025.11.25.25340489v1 A structure-informed deep learning framework for modeling TCR-peptide
-
of the fundamentals of deep learning and experience in creating datasets for training AI models would be a valuable asset. Internal Application form(s) needed WA.1220-5-2026-ENG.pdf English (577.98 KB - PDF) Download
-
cycle assessment, life-cycle cost analysis, pavement simulation, machine learning, deep reinforcement learning, and/or physics-informed modeling frameworks; and demonstrated ability to effectively
-
learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
-
qualifications include: Strong research experience in deep learning and foundation models, including experience with pre-trained models, fine-tuning, transfer learning, or self-supervised learning. Experience with
-
. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning
-
as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop