Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Sweden
- Germany
- Norway
- Denmark
- France
- Netherlands
- Spain
- Austria
- Luxembourg
- Poland
- Belgium
- United Kingdom
- China
- Portugal
- Singapore
- Switzerland
- Canada
- Finland
- Czech
- Ireland
- Italy
- Romania
- Saudi Arabia
- Cyprus
- Slovenia
- United Arab Emirates
- Worldwide
- Andorra
- Brazil
- Bulgaria
- Hong Kong
- Japan
- Latvia
- Taiwan
- 25 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Science
- Engineering
- Economics
- Mathematics
- Humanities
- Chemistry
- Linguistics
- Materials Science
- Physics
- Earth Sciences
- Electrical Engineering
- Psychology
- Arts and Literature
- Education
- Law
- Environment
- Business
- Sports and Recreation
- Design
- Philosophy
- 13 more »
- « less
-
the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
-
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
-
discipline. Experience with deep learning framework PyTorch or similar. Strong background in machine learning, image or signal processing. Knowledge of SotA models for multi-modality and scene understanding
-
mixed-methods research considered an asset. Experience in dealing with multiple commitments, short deadlines and sensitive clinical or research issues Intermediate or advanced computer skills in
-
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
-
and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your skills in over 600 courses
-
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
-
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
-
with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
-
. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE