Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Oak Ridge National Laboratory
- Nature Careers
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stony Brook University
- Chalmers University of Technology
- Argonne
- Aarhus University
- Cornell University
- Rutgers University
- Brookhaven National Laboratory
- European Space Agency
- Indiana University
- Institut Pasteur
- Leibniz
- NEW YORK UNIVERSITY ABU DHABI
- The University of Arizona
- University of Florida
- Aalborg University
- Argonne National Laboratory
- Austrian Academy of Sciences, the Austrian Archaeological Institute OeAI
- Biobizkaia Health Research Institute
- Blekinge Institute of Technology
- CNRS
- Consejo Superior de Investigaciones Científicas
- Delft University of Technology (TU Delft)
- Duke University
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Empa
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- Forschungszentrum Jülich
- Fudan University
- ICN2
- Institute of Theoretical Physics
- Jönköping University
- Lawrence Berkeley National Laboratory
- Lodz University of Technology
- Massachusetts Institute of Technology
- New York University
- Northeastern University
- Sandia National Laboratories
- Technical University of Munich
- Texas A&M University
- University College Cork
- University of Aveiro
- University of Luxembourg
- University of Miami
- University of North Carolina at Chapel Hill
- University of Oslo
- University of St. Thomas
- Université côte d'azur
- Université de Strasbourg
- VIB
- 43 more »
- « less
-
Field
-
high-fidelity qubit control and further ingredients for a shuttling-based architecture, using devices from academic or industrial fabrication. Key activities can include: Demonstration and experimental
-
). The team focuses on the development and design of reliable, safe, and secure software systems, carrying out both upstream activities such as requirements quality assurance and architecture analysis, as
-
trustworthy AI for science. At Eindhoven University of Technology (TU/e), you will contribute to the project’s core technical components: scientific data orchestration and knowledge graphs architecture and
-
. Responsibilities Model Development: Build and train advanced deep learning architectures (e.g., CNNs, Transformers, Generative Models) to decode the regulatory logic of genomic enhancers in GBM
-
deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
-
using software, such as LAMMPS, and machine-learned potentials Experience in GPU programming with Kokkos An understanding of computer architecture and experience in the analysis and improvement
-
the main bioinformatics software and methods (R, Python, Bash). Knowledge on large-scale genotyping/sequencing data analyses. Good level in statistics. Good level of written and oral English. Ease in a
-
software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
-
the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB + thermal wound images
-
/ML models and hardware/software co-design for AI applications. ● Radiation testing of electronic systems, with an emphasis on single event effects. Preferred Qualifications: ● Experience in