Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Sweden
- Germany
- Norway
- Denmark
- France
- Netherlands
- Austria
- Poland
- Spain
- United Kingdom
- Luxembourg
- Belgium
- Singapore
- Finland
- Switzerland
- Canada
- Portugal
- China
- Czech
- Ireland
- Italy
- Romania
- Saudi Arabia
- Cyprus
- Bulgaria
- Slovenia
- United Arab Emirates
- Worldwide
- Andorra
- Brazil
- Hong Kong
- Japan
- Latvia
- Taiwan
- 25 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Science
- Engineering
- Economics
- Mathematics
- Humanities
- Chemistry
- Linguistics
- Materials Science
- Earth Sciences
- Physics
- Electrical Engineering
- Psychology
- Arts and Literature
- Education
- Environment
- Law
- Business
- Sports and Recreation
- Design
- Philosophy
- 13 more »
- « less
-
by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
-
for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
-
and simulation Prior experience with particle accelerators and/or FELs is highly desirable Familiarity with machine learning techniques is a plus but not necessary Excellent command of English is
-
modeling approaches-including machine learning (ML), hydrologic and energy systems simulations, and scenario forecasting-to evaluate dynamic energy-water futures and resilience strategies for diverse Idaho
-
for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation
-
minimizing computational and energy costs. The proposed approaches will rely on machine learning methods applied to image analysis, with the objective of enabling early identification of at risk areas and
-
environment where machine learning meets real-world scientific impact. What You’ll Do: Conduct cutting-edge research at the intersection of AI and science Develop large-scale deep learning models for scientific
-
environments, and assessing model explainability. You'll work closely with a team of graduate students, postdocs, and other collaborators to develop innovative AI models, create software tools, and establish
-
on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
-
to the fundamentals of spatiotemporal data science and machine learning using scripting languages. Supervise BSc and MSc thesis students conducting research in Geo-information Science. You will work here The research