Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Susquehanna International Group
- ;
- AALTO UNIVERSITY
- Technical University of Munich
- Carnegie Mellon University
- Imperial College London
- Nature Careers
- Radix Trading LLC
- UNIVERSITY OF HELSINKI
- Universite de Moncton
- University of Cambridge
- University of Nebraska–Lincoln
- Binghamton University
- Cornell University
- Cracow University of Technology
- Drexel University
- Heraeus Covantics
- McGill University
- National Institute for Bioprocessing Research and Training (NIBRT)
- National Renewable Energy Laboratory NREL
- Northeastern University
- Purdue University
- SINTEF
- Technical University of Denmark
- University of Alabama, Tuscaloosa
- University of Antwerp
- University of California Irvine
- University of Cambridge;
- University of Luxembourg
- University of New Hampshire – Main Campus
- University of Newcastle
- University of Texas at El Paso
- University of Tübingen
- University of Utah
- Virginia Tech
- 25 more »
- « less
-
Field
-
achievements in the field of physical sciences documented by publications in renowned journals 2. Additional Requirements: 1) statistical analysis of large data sets 2) knowledge of machine learning 3
-
locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
-
+to+apply#Howtoapply-Eligibility) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science, Psychology or a related field excellent knowledge in AI and at least one
-
at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science
-
drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
-
knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
-
University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
-
operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
-
engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
-
Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and