Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Norway
- Germany
- France
- Netherlands
- Denmark
- Belgium
- Austria
- Singapore
- Hong Kong
- Australia
- Poland
- Spain
- Estonia
- Portugal
- Switzerland
- United Arab Emirates
- China
- Italy
- Luxembourg
- Canada
- Cyprus
- Czech
- Finland
- Barbados
- Brazil
- Europe
- Iceland
- Ireland
- Japan
- Lithuania
- Morocco
- New Zealand
- Saudi Arabia
- Taiwan
- Worldwide
- 28 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Biology
- Science
- Economics
- Mathematics
- Psychology
- Humanities
- Materials Science
- Chemistry
- Environment
- Linguistics
- Arts and Literature
- Earth Sciences
- Education
- Electrical Engineering
- Business
- Physics
- Social Sciences
- Sports and Recreation
- Law
- 12 more »
- « less
-
Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs). Extensive Knowledge In: • First-principles atomistic simulations with packages
-
deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
-
. Your work may also include teaching or other departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level in Mathematics, Computer/Data
-
recording. The work will also include developing new statistical data analysis tools for behavioral and neural data. More broadly, the postdoc will be part of a large and intellectually vibrant community
-
the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
-
modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in or experience in environmental exposure
-
. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
-
and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
-
management Machine learning, artificial intelligence, and big data analytics in finance Technological innovations for financial services Regulatory issues and challenges in FinTech Digital economy and
-
, Jose Landivar-Scott, Nick Duffield, Kevin Nowka, Jinha Jung, Anjin Chang, Kiju Lee, Lei Zhao, Mahendra Bhandari, Unmanned aerial system and machine learning driven Digital-Twin framework for in-season