Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Susquehanna International Group
- ;
- AALTO UNIVERSITY
- Technical University of Munich
- Carnegie Mellon University
- Imperial College London
- Radix Trading LLC
- UNIVERSITY OF HELSINKI
- Universite de Moncton
- University of Cambridge
- Binghamton University
- Heraeus Covantics
- National Institute for Bioprocessing Research and Training (NIBRT)
- National Renewable Energy Laboratory NREL
- Nature Careers
- Northeastern University
- SINTEF
- Technical University of Denmark
- University of Antwerp
- University of California Irvine
- University of Cambridge;
- University of Luxembourg
- University of Newcastle
- University of Tübingen
- University of Utah
- 15 more »
- « less
-
Field
-
), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
-
qualification you must hold a PhD degree (or equivalent). Specifically, a PhD in manufacturing engineering (or equivalent) with documented experience in the following areas: Precision machining Machining system
-
, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
-
. Knowledge on multiphase (gas-particle two phase system), thermal energy storage, and/or renewable hydrogen technologies. Familiar with application of machine learning and deep learning algorithms to fluid and
-
, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug development. The successful candidate will contribute
-
to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
-
the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
-
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
-
) Developing machine-learning based exoskeleton controllers to work across tasks 2) Designing and validating new robotic lower-limb prostheses 3) Exploring other high-risk high-reward research areas related
-
+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