Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- France
- Norway
- Portugal
- Singapore
- Netherlands
- Spain
- Belgium
- Denmark
- United Arab Emirates
- China
- Italy
- Australia
- Canada
- Switzerland
- Luxembourg
- Hong Kong
- Austria
- Finland
- Ireland
- Czech
- Poland
- Japan
- Romania
- Estonia
- Brazil
- Latvia
- Morocco
- Cyprus
- India
- Saudi Arabia
- Lithuania
- South Africa
- Andorra
- Greece
- Taiwan
- Israel
- Slovenia
- Armenia
- Barbados
- Europe
- Iceland
- Malta
- Mexico
- New Zealand
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Social Sciences
- Arts and Literature
- Chemistry
- Humanities
- Earth Sciences
- Linguistics
- Environment
- Sports and Recreation
- Law
- Electrical Engineering
- Physics
- Design
- Philosophy
- 14 more »
- « less
-
. The positions focus on applied machine learning methods for real-world systems. Possible research directions include: Transfer learning and domain adaptation across heterogeneous production environments (e.g
-
Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model
-
. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
-
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 8 days ago
. Build statistical and machine-learning models to infer RNA regulatory networks and developmental splicing programs, translating results into experimentally testable hypotheses. Your profile Master's
-
Proficiency in at least one programming language, preferably Python; experience with scientific computing, numerical modeling, or machine-learning frameworks is an asset Strong analytical skills with a solid
-
intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
-
of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD
-
software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
-
-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
-
predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time