Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Stanford University
- Delft University of Technology (TU Delft)
- Oak Ridge National Laboratory
- University of North Carolina at Chapel Hill
- University of Oxford
- Cornell University
- EPFL
- Harvard University
- Pennsylvania State University
- Technical University of Munich
- University of Florida
- Utrecht University
- Duke University
- New York University
- SciLifeLab
- Yale University
- Argonne
- Empa
- FAPESP - São Paulo Research Foundation
- KTH Royal Institute of Technology
- NEW YORK UNIVERSITY ABU DHABI
- National Energy Technology Laboratory (NETL)
- Northeastern University
- UNIVERSITY OF VIENNA
- University of Texas at Arlington
- University of Washington
- AALTO UNIVERSITY
- Aalborg University
- Aarhus University
- Baylor College of Medicine
- Baylor University
- CNRS
- Carnegie Mellon University
- Chalmers University of Technology
- European Space Agency
- ICN2
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Istituto Italiano di Tecnologia
- Maastricht University (UM)
- Massachusetts Institute of Technology
- Queen Mary University of London
- Queen Mary University of London;
- Singapore-MIT Alliance for Research and Technology
- Stony Brook University
- Texas A&M AgriLife
- Texas A&M University
- The Ohio State University
- UNIVERSITY OF HELSINKI
- University of Miami
- University of Minnesota
- University of Oxford;
- Virginia Tech
- Vrije Universiteit Brussel
- ;
- Austrian Academy of Sciences, The Marietta Blau Instiute (MBI)
- Beijing Academy of Quantum Information Sciences
- Computer Vision Center
- Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke
- Forschungszentrum Jülich
- Fundació per a la Universitat Oberta de Catalunya
- Human Technopole
- INSERM
- IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences)
- Imperial College London
- Indiana University
- KU LEUVEN
- King Abdullah University of Science and Technology
- Lancaster University
- Lehigh University
- Lunds universitet
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS)
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
- Missouri University of Science and Technology
- National Aeronautics and Space Administration (NASA)
- Norwegian University of Life Sciences (NMBU)
- RIKEN
- Radboud University Medical Center (Radboudumc)
- Research Center for Molecular Medicine (CeMM), ÖAW
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Saarland University
- THE UNIVERSITY OF HONG KONG
- Texas A&m Engineering
- The University of Iowa
- Tsinghua University
- Télécom Paris
- U.S. Department of Energy (DOE)
- UNIVERSIDAD POLITECNICA DE MADRID
- Umeå University
- University College Dublin
- University of British Columbia
- University of California
- University of California Irvine
- University of Canterbury
- University of Illinois at Chicago
- University of Liège
- University of London
- University of Lund
- 90 more »
- « less
-
Field
-
in creating and evaluating machine learning models.•Familiarity with deep learning framework, such as PyTorch or Tensorflow.•Experience in data preparation, preferably in a bioinformatics context (data
-
; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
-
avenues of research rather than a required work plan. They may be pursued individually or in combination, and we welcome other creative and strategic approaches. Statistical or machine-learning approaches
-
postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
-
programming languages is required, and experience with the current ATLAS software, computing and particularly the tracking software would be particularly desirable. Experience with machine learning and
-
on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
-
. - Strong expertise in multiscale/multiphysics modeling relevant to catalysis, and experience with machine learning models. - Deep understanding of reaction kinetics, thermodynamics, and structure-reactivity
-
of machine learning techniques, programming and coding for data analysis, biomarker discovery, and collaboration with clinicians and students. Additionally, the candidate will be responsible for grant writing
-
on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
-
on machine learning, deep learning, control systems, sensing systems, and related technologies. Supports the development, testing, and transition of emerging autonomous technologies through laboratory