Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Carnegie Mellon University
- Susquehanna International Group
- ;
- Nature Careers
- University of Newcastle
- University of Utah
- Duke University
- Radix Trading LLC
- Technical University of Denmark
- Technical University of Munich
- Temple University
- University of Cambridge
- Forschungszentrum Jülich
- Marquette University
- McGill University
- MedUni Vienna
- National Institute for Bioprocessing Research and Training (NIBRT)
- Trinity College Dublin
- University of Luxembourg
- University of Oslo
- University of Pennsylvania
- Vrije Universiteit Brussel
- Wageningen University & Research
- 13 more »
- « less
-
Field
-
impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and
-
impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and
-
Generative Models" (UCL , Oxford, Imperial, Edinburgh, Cardiff, Manchester and Surrey) and with its industrial partners. Key responsibilities include working on deep learning, probabilistic modelling, deep
-
Generative Models" (UCL , Oxford, Imperial, Edinburgh, Cardiff, Manchester and Surrey) and with its industrial partners. Key responsibilities include working on deep learning, probabilistic modelling, deep
-
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
-
control subjects based on diffusion MRI images and functional MRI responses. Duties include: Developing machine-learning and/or deep learning pipelines for classifying patients of optic neuropathies and
-
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
-
Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
-
characterization of deep-water habitats, GIS spatial analysis of species distribution data, and quantification of ecosystem services. Preference will be given to applicants that possess a diverse set of skills and
-
Professor that will be capable of contributing to multiple ongoing research projects in the lab. Potential projects include, but are not limited to, oceanographic characterization of deep-water habitats, GIS