Sort by
Refine Your Search
-
Listed
-
Country
- United States
- United Kingdom
- Sweden
- France
- Germany
- Belgium
- Poland
- China
- Austria
- Spain
- Australia
- Canada
- Netherlands
- Denmark
- Hong Kong
- Singapore
- Italy
- Portugal
- India
- Czech
- Latvia
- Cyprus
- Ireland
- Luxembourg
- Andorra
- Lithuania
- South Africa
- Bulgaria
- Estonia
- United Arab Emirates
- Armenia
- New Zealand
- Norway
- Saudi Arabia
- Switzerland
- Barbados
- Croatia
- Europe
- Greece
- Japan
- Malta
- Morocco
- Slovenia
- Worldwide
- 34 more »
- « less
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Mathematics
- Business
- Social Sciences
- Arts and Literature
- Psychology
- Education
- Humanities
- Chemistry
- Electrical Engineering
- Linguistics
- Materials Science
- Environment
- Physics
- Design
- Earth Sciences
- Sports and Recreation
- Philosophy
- Law
- 14 more »
- « less
-
Science, Machine Learning, Computational Linguistics or a related field, if applicable with PhD previous experience in Natural Language Processing, knowledge Graphs, Machine Learning or Recommender Systems
-
domains (e.g., automotive, human-computer interaction), where efficient on-device processing is essential. We are looking for a highly motivated PhD researcher with an interest in hardware-aware
-
confirmed PhD commencement date: To be confirmed Project Key Words: Machine Translation, Natural Language Processing, Terminology Translation, Agentic RAG Post summary We are looking for a candidate for a
-
the undergraduate and graduate levels. Where to apply Website https://www.bth.se/english/vacancies/job/phd-student-position-in-software-engin… Requirements Research FieldComputer science » Computer systemsEducation
-
/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in
-
to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust, interpretable models from experimental and operational data
-
: comparative omics, genetic diversity analysis, mathematical modelling, machine learning, and the use of model organisms. Develop transferable skills such as scientific communication, project management
-
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The aim is to develop machine-learning models that describe how
-
to reduce the cost of clean hydrogen to $1/kg by 2031. The project proposes to address key scientific challenges by using molecular simulations (reactive force fields like ReaxFF and machine learning
-
with artificial intelligence (machine learning/deep learning) Essential Application/interview Experience with classical image processing techniques (e.g. classification/segmentation/registration