Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Germany
- Netherlands
- Spain
- Portugal
- France
- Singapore
- Norway
- Denmark
- United Arab Emirates
- Belgium
- Switzerland
- China
- Australia
- Finland
- Italy
- Poland
- Luxembourg
- Canada
- Hong Kong
- Austria
- Morocco
- Vietnam
- Ireland
- Romania
- Czech
- Japan
- Estonia
- Greece
- Brazil
- Cyprus
- Saudi Arabia
- Croatia
- Lithuania
- Andorra
- India
- South Africa
- Taiwan
- Latvia
- Malta
- New Zealand
- Slovenia
- Worldwide
- Hungary
- Israel
- Kenya
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Earth Sciences
- Arts and Literature
- Chemistry
- Environment
- Social Sciences
- Humanities
- Linguistics
- Electrical Engineering
- Sports and Recreation
- Law
- Physics
- Philosophy
- Design
- Statistics
- 15 more »
- « less
-
courses). - Proficiency with computer tools: R, Python, Bash, Perl, Java, SQL. - English: High-level language proficiency. - Willingness, ability to learn, and teamwork skills will be valued. - Experience
-
computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
-
adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low
-
machine learning models to estimate individual numbers and distinguish species in complex field conditions. The resulting methods could later be applied to monitor waterfowl and scavengers in Lough Neagh
-
should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
-
-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
-
, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
-
) Neuromodulation approaches (TMS, tDCS, TUS) Neurogenetics Computational modelling (machine learning, reinforcement learning) Our research bridges scales (local circuits to global networks) and species (humans, mice
-
developing innovative solutions for integrating geophysical data and machine learning approaches for geological modelling and site characterization. The position is expected to perform independent and
-
Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech