Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- UNIVERSITY OF VIENNA
- Aarhus University
- Argonne
- University of North Carolina at Chapel Hill
- Stony Brook University
- Technical University of Munich
- Technical University of Denmark
- University of California Berkeley
- University of Oxford
- Duke University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stanford University
- University of Minnesota
- Brookhaven National Laboratory
- Lunds universitet
- Macquarie University
- University of Amsterdam (UvA)
- University of Luxembourg
- University of Washington
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- CNRS
- Carnegie Mellon University
- Czech Technical University in Prague
- ETH Zürich
- European Space Agency
- IMT Atlantique
- Institut Pasteur
- Institut de Físiques d'Altes Energies (IFAE)
- NEW YORK UNIVERSITY ABU DHABI
- New York University
- Northeastern University
- Oak Ridge National Laboratory
- South Dakota Mines
- THE UNIVERSITY OF HONG KONG
- The University of Iowa
- University of Antwerp
- University of Basel
- University of Lund
- University of Miami
- AALTO UNIVERSITY
- Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf
- Constructor University Bremen gGmbH
- Copenhagen Business School
- Cornell University
- Delft University of Technology (TU Delft)
- ERATOSTHENES CENTRE OF EXCELLENCE
- Eindhoven University of Technology (TU/e)
- European Magnetism Association EMA
- Flanders Institute for Biotechnology
- Fondazione Bruno Kessler
- Free University of Berlin
- GFZ Helmholtz-Zentrum für Geoforschung
- George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș
- Harvard University
- Helmholtz Zentrum Hereon
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Hong Kong Polytechnic University
- ICN2
- IMT - Institut Mines-Télécom
- IMT Mines Ales
- IMT Nord Europe
- Institute of Physical Chemistry, Polish Academy of Sciences
- Instituto de Engenharia Mecânica
- Istituto Italiano di Tecnologia
- King's College London
- Leibniz
- Luxembourg Institute of Science and Technology
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- McGill University
- Pennsylvania State University
- Purdue University
- Rutgers University
- SUNY University at Buffalo
- San Diego State University
- Sandia National Laboratories
- Singapore-MIT Alliance for Research and Technology
- Texas A&M University
- The Ohio State University
- The University of North Carolina at Chapel Hill
- Tufts University
- Télécom Paris
- UNIVERSITE D'ORLEANS
- Umeå University
- Umeå universitet
- University of British Columbia
- University of Cambridge;
- University of Canterbury
- University of Canterbury, New Zealand;
- University of Colorado
- University of Nebraska Medical Center
- University of Nevada Las Vegas
- University of Oxford;
- University of Southern Denmark
- University of Sydney
- University of Texas at Arlington
- University of Utah
- University of Vienna
- 90 more »
- « less
-
Field
-
evaluate innovative methods based on generative models and Vision-Language Models. Design, implement, and validate deep learning approaches for vision applications. Publish research results in leading
-
deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in
-
the long term. Is Your profile described below? Are you our future colleague? Apply now! Education PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote
-
analysing multimodal deep learning models for time-specific cancer risk and time-to-event prediction by integrating imaging with longitudinal Electronic Health Record (EHR) signals. Building scalable
-
, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
-
projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
-
at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will
-
FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science. Experience with multimodal models for biological data. Website
-
. • Contribute to interdisciplinary research projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep
-
predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time