Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- Netherlands
- France
- Denmark
- Norway
- Spain
- Portugal
- Belgium
- Australia
- United Arab Emirates
- Switzerland
- Poland
- Singapore
- Austria
- China
- Canada
- Hong Kong
- Luxembourg
- Finland
- Czech
- Vietnam
- Ireland
- Morocco
- Italy
- Romania
- Estonia
- India
- Andorra
- Brazil
- Croatia
- Cyprus
- Latvia
- Lithuania
- New Zealand
- South Africa
- Greece
- Slovenia
- Ukraine
- Chile
- Japan
- Saudi Arabia
- Armenia
- Bulgaria
- Indonesia
- Israel
- Kenya
- Qatar
- Taiwan
- Worldwide
- 42 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Economics
- Biology
- Science
- Mathematics
- Chemistry
- Arts and Literature
- Social Sciences
- Business
- Psychology
- Education
- Humanities
- Materials Science
- Earth Sciences
- Electrical Engineering
- Environment
- Linguistics
- Law
- Physics
- Design
- Philosophy
- Sports and Recreation
- Statistics
- 15 more »
- « less
-
, funded by a Leverhulme Trust Research Leadership Award held by Dr Alessio Spurio Mancini. ECLIPSE's goal is to develop next-generation inference frameworks that combine machine learning with rigorous
-
the supervision of the PI, including proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. Pursue research topics
-
quantification in science, engineering, and machine learning. Your workplace You will be employed at the Division of Applied Mathematics in a welcoming and international work environment. The research group in
-
. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
-
at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
-
that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
-
proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
-
, traditional planning often fails to capture workload variability, uncertainty, and the complex interaction between product features, labor availability, and machine capacity. Your PhD will address
-
Kepler University Linz (JKU). Check out the detailed announcement on our homepage: https://www.pro2future.at/phd-candidate-within-the-topic-ai-driven-software-instrumentation/ Where to apply E-mail jobs
-
and/or the CAD/CAM process is a plus. I am proficient in Python and am familiar with data science and machine/deep learning toolkits. As a PhD researcher at KU Leuven, I perform research in a structured