924 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" uni jobs at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Country
- United States
- Austria
- Germany
- United Kingdom
- Spain
- India
- Worldwide
- Denmark
- France
- Canada
- Mexico
- South Africa
- Hong Kong
- Switzerland
- Sweden
- Belgium
- Italy
- Singapore
- Australia
- Luxembourg
- United Arab Emirates
- Finland
- Netherlands
- Poland
- South Korea
- Argentina
- Barbados
- Guadeloupe
- Israel
- Japan
- Norway
- Portugal
- Taiwan
- Vietnam
- 24 more »
- « less
-
Field
-
science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more
-
Cloverdale, KPU is deeply connected to the communities it serves and to the diverse cultures, backgrounds, and lived experiences of its students. Through academic excellence, applied learning, innovation, and
-
. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
-
tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
-
. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
-
postdoctoral research track record and are expected to build and lead a group to pursue a high-quality research programme. Current research interests within the Division of Condensed Matter Theory (https
-
Shanghai Jiao Tong University Global Recruitment Shanghai Jiao Tong University (SJTU) is one of theprestigious higher education institutions of higher learning with the longest history and
-
to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more information, please visit
-
Design and use of data spaces and digital twins for materials and autonomous material laboratories Use of deep learning methods to connect theory, simulation, and experiments Integration of high throughput
-
Tenure-Track Faculty Position in Microelectronics and Photonics (Teaching-Focused) The Department of Electrical and Computer Engineering Stephen J.R. Smith Faculty of Engineering and Applied