Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- Netherlands
- Denmark
- France
- Norway
- Spain
- Portugal
- Belgium
- Australia
- United Arab Emirates
- Switzerland
- Poland
- Singapore
- Austria
- China
- Canada
- Hong Kong
- Luxembourg
- Finland
- Czech
- Vietnam
- Ireland
- Morocco
- Romania
- Estonia
- Italy
- India
- Andorra
- Brazil
- Croatia
- Cyprus
- Latvia
- Lithuania
- New Zealand
- South Africa
- Greece
- Slovenia
- Ukraine
- Chile
- Japan
- Armenia
- Bulgaria
- Indonesia
- Israel
- Kenya
- Qatar
- Saudi Arabia
- 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
-
simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical
-
: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
-
cameras, heart rate monitors, and dedicated activity trackers for data collection and employ relevant machine learning methods for data analysis and sensor fusion. The PhD Research Fellow will collaborate
-
Job type: Principal Investigator Qualification: PhD Job duration: fixed 5-year term (can be extended for additional 4-years upon positive evaluation) Job hours: full-time Discipline: Life Sciences
-
. This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions
-
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
-
The logic and learning (LOL) group is recruiting a PhD student funded by ELLIS institute Finland. You will work with Associate Professor Andrew Cropper . We work on combining logical reasoning and
-
(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
-
Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics
-
package, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https