Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nanyang Technological University
- ;
- Nature Careers
- National University of Singapore
- AbbVie
- KINGS COLLEGE LONDON
- King's College London
- UiT The Arctic University of Norway
- University of Birmingham
- University of Oslo
- Monash University
- Singapore Institute of Technology
- The University of Queensland
- University of Alabama, Tuscaloosa
- University of New South Wales
- CRANFIELD UNIVERSITY
- Curtin University
- Harvard University
- NTNU - Norwegian University of Science and Technology
- Northeastern University
- Simons Foundation
- University of Bergen
- University of British Columbia
- University of Cambridge
- University of Michigan
- University of Stavanger
- Western Norway University of Applied Sciences
- Zintellect
- ; King's College London
- Arizona State University
- Central Michigan University
- Colorado State University
- Cornell University
- George Mason University
- Humboldt-Stiftung Foundation
- Imperial College London
- Johns Hopkins University
- LINGNAN UNIVERSITY
- Manchester Metropolitan University
- Marquette University
- QUEENS UNIVERSITY BELFAST
- RMIT University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Stanford University
- The University of Alabama
- The University of Southampton
- UNIVERSITY OF SOUTHAMPTON
- UNIVERSITY OF SURREY
- University of Adelaide
- University of Agder
- University of Leeds
- University of Liverpool
- University of Surrey
- University of Texas at Austin
- University of Waterloo
- 45 more »
- « less
-
Field
-
organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data
-
be responsible for an extensive laboratory campaign in the Large Water Channel (Jooss et al. 2020, J. Fluid Mech. 911, A4 ), in close collaboration with several other postdocs and PhD students
-
will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
-
one of the following areas is required: Numerical methods for large-scale, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and
-
qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
-
++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
-
requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
-
, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
-
/or machine learning methods, and an interest in applying these tools to urban and housing policy questions. The Fellow should demonstrate potential for producing high-quality research and a strong
-
UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able