Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- ;
- Susquehanna International Group
- Carnegie Mellon University
- Cornell University
- Duke University
- Imperial College London
- Technical University of Munich
- Arizona State University
- Brookhaven Lab
- Fraunhofer-Gesellschaft
- Leibniz
- McGill University
- National Institute for Bioprocessing Research and Training (NIBRT)
- Nature Careers
- Purdue University
- Technical University of Denmark
- The University of Chicago
- University of California Irvine
- University of Lethbridge
- University of Luxembourg
- University of Massachusetts Medical School
- University of Minnesota
- University of Newcastle
- University of Tübingen
- University of Utah
- Vrije Universiteit Brussel
- 16 more »
- « less
-
Field
-
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
-
deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature
-
-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning
-
We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
-
strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
-
Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
-
capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
-
Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
-
Europe | 20 days ago
manufacturing, development of machine learning algorithms and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen
-
/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming