Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- Technical University of Munich
- Technical University of Denmark
- Nature Careers
- Curtin University
- DAAD
- Forschungszentrum Jülich
- Susquehanna International Group
- Leiden University
- Radboud University
- Delft University of Technology (TU Delft); Delft
- Lulea University of Technology
- CNRS
- Leibniz
- University of Nottingham
- University of Southern Denmark
- University of Utah
- ;
- ; The University of Manchester
- CWI
- Carnegie Mellon University
- Ghent University
- Inria, the French national research institute for the digital sciences
- Leiden University; Leiden
- Linköping University
- Monash University
- NTNU - Norwegian University of Science and Technology
- Radix Trading LLC
- SciLifeLab
- Temple University
- UNIVERSITY OF HELSINKI
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Amsterdam
- University of British Columbia
- University of Florida
- University of Groningen
- University of Sheffield
- University of Twente
- University of Twente (UT)
- Uppsala universitet
- VIB
- Vrije Universiteit Brussel
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Newcastle University
- ; University of Exeter
- ; University of Surrey
- ; University of Warwick
- Abertay University
- Agricultural university - Plovdiv, Bulgaria
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Chalmers University of Technology
- Copenhagen Business School , CBS
- Coventry University Group;
- Delft University of Technology (TU Delft)
- Duke University
- Eindhoven University of Technology (TU/e)
- Helmholtz-Zentrum München
- Imperial College London
- Instituto Superior de Economia e Gestão
- La Trobe University
- McGill University
- Medizinische Universitaet Wien
- Murdoch University
- National Renewable Energy Laboratory NREL
- National Research Council Canada
- Norwegian Meteorological Institute
- Queensland University of Technology
- Reykjavik University
- SINTEF
- Singapore Institute of Technology
- Swinburne University of Technology
- Technische Universität München
- UCT Prague
- UNIVERSIDAD POLITECNICA DE MADRID
- University of Adelaide
- University of California Irvine
- University of Cambridge
- University of Exeter
- University of Luxembourg
- University of Massachusetts Medical School
- University of Melbourne
- University of Newcastle
- University of Southern Queensland
- University of Texas at El Paso
- University of Twente (UT); Enschede
- University of Vienna
- University of Warwick
- Université Laval
- 80 more »
- « less
-
Field
-
deep learning, preferably including some exposure to graph neural networks or geometric deep learning. Proven experience with implementing machine learning methods in Python and Pytorch. Familiarity with
-
this project, you will combine a deep knowledge of physical chemistry with robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning
-
of topics is covered, from large-scale data management to data mining and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics
-
positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
-
complete) an M.Sc. (or equivalent) in Computer Science or a related discipline ML expertise: You have strong programming and deep learning experience (e.g., PyTorch, TensorFlow), backed by a substantial
-
). The candidate should have hands-on experience developing state-of-the-art machine learning models, particularly deep neural networks (experience with graph neural networks is highly valued). Their background
-
, for example, Machine Learning, Deep Learning, Artificial Intelligence, Information Security, or related subjects. Alternatively, you have gained essentially corresponding knowledge in another way. The position
-
to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
-
apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
-
Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still