Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- Technical University of Munich
- SciLifeLab
- ;
- Curtin University
- Technical University of Denmark
- DAAD
- Nature Careers
- Susquehanna International Group
- Leibniz
- Lulea University of Technology
- Chalmers University of Technology
- Fraunhofer-Gesellschaft
- Ghent University
- University of Southern Denmark
- University of Utah
- ; The University of Manchester
- ; University of Warwick
- CWI
- Carnegie Mellon University
- Forschungszentrum Jülich
- Monash University
- Radboud University
- Radix Trading LLC
- Temple University
- University of Luxembourg
- University of Newcastle
- Utrecht University
- Vrije Universiteit Brussel
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Newcastle University
- ; University of Copenhagen
- ; University of Exeter
- ; University of Leeds
- ; University of Nottingham
- ; University of Surrey
- Aalborg University
- Abertay University
- Copenhagen Business School , CBS
- Duke University
- Imperial College London
- Leiden University
- McGill University
- NTNU - Norwegian University of Science and Technology
- National Institute for Bioprocessing Research and Training (NIBRT)
- National Research Council Canada
- Norwegian Meteorological Institute
- Queensland University of Technology
- Singapore Institute of Technology
- Swinburne University of Technology
- The University of Alabama
- University of British Columbia
- University of California Irvine
- University of Groningen
- University of Nottingham
- University of Sheffield
- University of Southern Queensland
- University of Texas at El Paso
- University of Vienna
- 51 more »
- « less
-
Field
-
shift in the world of hardware design. On the one hand, the increasing complexity of deep-learning models demands computers faster and more powerful than ever before. On the other hand, the numerical
-
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
-
: You will be responsible for the sensor system and the perception algorithms of an autonomous mobile robot. You will engage in research around deep learning and 2D/3D computer vision for a well-defined
-
the molecular level. While structural predictions using deep learning methods like AlphaFold have revolutionized our understanding of sequence dependent molecular structure, we currently have much more limited
-
need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
-
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
-
, an extensive training programme in respect of industry-specific skills, and access to hotfire facilities at Westcott, Machrihanish, and elsewhere. You can learn more about the programme at r2t2.org.uk. Kick
-
solutions need to be safe and accurate. Aim This project will focus on investigating and developing new ways in which deep learning-based solutions can continuously learn and deal with unseen situations, with
-
of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
-
effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions