Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nanyang Technological University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Oslo
- Macquarie University
- National University of Singapore
- Harvard University
- Indiana University
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- City of Hope
- Monash University
- University of Arkansas
- University of Michigan
- Zintellect
- King Abdullah University of Science and Technology
- University of California
- University of Nottingham
- Center for Drug Evaluation and Research (CDER)
- Cornell University
- Hong Kong Polytechnic University
- Northeastern University
- Singapore University of Technology & Design
- Universidade do Minho
- University of Algarve
- University of British Columbia
- University of Maryland, Baltimore
- University of New South Wales
- University of Sheffield
- Wayne State University
- ;
- Aarhus University
- CRANFIELD UNIVERSITY
- Carnegie Mellon University
- Center for Devices and Radiological Health (CDRH)
- Centre for European Policy Studies
- Centro de Engenharia Biológica da Universidade do Minho
- Dalhousie University
- Dana-Farber Cancer Institute (DFCI)
- European Space Agency
- Fields Institute
- Francis Crick Institute
- INESC ID
- INESC TEC
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Johns Hopkins University
- King's College London
- Lund University
- Marquette University
- Max Planck Institute of Biochemistry, Martinsried
- Max-Planck-Institut für Bildungsforschung
- Mayo Clinic
- NTNU Norwegian University of Science and Technology
- SUNY University at Buffalo
- SciLifeLab
- St Jude Children's Research Hospital
- Stephen & Denise Adams Center for Parkinson's Disease at Yale School of Medicine
- Technical University of Munich
- The Francis Crick Institute;
- The University of Queensland
- The University of Southampton
- Tokyo University of Science
- UCL EE
- UCL;
- UNIVERSITY OF MELBOURNE
- UNIVERSITY OF NOTTINGHAM NINGBO CHINA
- UiT The Arctic University of Norway
- University Of The Arts London;
- University of Agder
- University of Beira Interior
- University of Bergen
- University of Birmingham
- University of California, Los Angeles
- University of Colorado
- University of Manchester
- University of Minho
- University of Newcastle
- University of North Carolina at Charlotte
- University of Notre Dame
- University of St Andrews;
- University of Texas at Austin
- University of Waterloo
- University of the Arts London
- Utah Valley University
- Visterra, Inc.
- 73 more »
- « less
-
Field
-
related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated cardiomyocyte subtypes, cellular trajectories, and
-
include deep learning, reinforcement learning, differentiable modelling and inverse design. You will implement and evaluate these methods using experimental optical systems and work towards their
-
foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
-
Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
-
Computer Science, Artificial Intelligence, Mathematics, Engineering, or a related field. Entry level candidates with demonstrated expertise in artificial intelligence (AI), machine learning, deep learning
-
minimum qualifications at the time of hire. PhD in computer science, data science, or related discipline Track record of publications in Artificial Intelligence and Deep Learning in peer-reviewed
-
, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
-
learning (“buddying”) Both roles will contribute to a developing cross-disciplinary Deep End research community Developing Skills & Expertise: Develop academic skills around research from design to delivery
-
processes under different biological conditions. Apply statistical learning, deep learning and probabilistic modelling approaches to large-scale cancer datasets. Evaluate and benchmark computational methods
-
The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims