Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Portugal
- France
- Netherlands
- Sweden
- Spain
- Denmark
- Singapore
- Belgium
- United Arab Emirates
- Italy
- Austria
- Norway
- Poland
- Finland
- Romania
- Australia
- Morocco
- Canada
- China
- Luxembourg
- Switzerland
- Hong Kong
- Japan
- Greece
- Brazil
- Croatia
- Estonia
- Cyprus
- Czech
- Malta
- Saudi Arabia
- Taiwan
- Bulgaria
- Ireland
- Israel
- Lithuania
- Andorra
- Armenia
- India
- New Zealand
- Slovakia
- Worldwide
- 35 more »
- « less
-
Program
-
Field
-
-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
-
an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
-
; apply the developed methodology to complex heterostructures The postdoctoral researcher will be recruited within the Chemical Theory and Modelling team (http://www.quanthic.org ) of the Institute
-
applications in astrophysics and/or Earth observation, with particular emphasis on the synthesis, interpretation, and modeling of large datasets. Where to apply Website https://apella.minedu.gov.gr/en/node/5999
-
computational algorithm and formulation for generating optimised structure and toolpaths while incorporating the manufacturing constraints. Candidate should have a PhD degree in Mechanical Engineering and strong
-
! This job offer is closely linked to a related opening at IET-3 at Forschungszentrum Jülich within the same project consortium: https://www.fz-juelich.de/en/careers/jobs/2025-362 Please feel free to apply
-
closely linked to a related opening at IMD-1 at Forschungszentrum Jülich within the same project consortium: https://www.fz-juelich.de/en/careers/jobs/2025-361 Please feel free to apply for both available
-
of this project for a one-year period (100% full-time commitment) to make a significant contribution to the implementation of machine learning (ML) algorithms. The postdoc is expected to have proven experience in
-
SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to kerstin.achtruth at tu-dresden.de or to: TU Dresden, Chair of Algorithms, Prof. Dr. László Kozma, Helmholtzstr. 10
-
testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs