Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Netherlands
- United Kingdom
- Sweden
- Germany
- Australia
- Norway
- Denmark
- Belgium
- Spain
- Luxembourg
- Singapore
- France
- United Arab Emirates
- Finland
- Portugal
- Switzerland
- Hong Kong
- Morocco
- Vietnam
- China
- Canada
- Cyprus
- Poland
- Austria
- Estonia
- Czech
- Italy
- Romania
- Lithuania
- Ireland
- Saudi Arabia
- Greece
- India
- New Zealand
- South Africa
- Taiwan
- Worldwide
- Germany / Finland
- Japan
- Macau
- Malta
- 32 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Economics
- Medical Sciences
- Biology
- Science
- Business
- Mathematics
- Materials Science
- Chemistry
- Arts and Literature
- Environment
- Earth Sciences
- Education
- Electrical Engineering
- Psychology
- Humanities
- Design
- Physics
- Linguistics
- Philosophy
- Social Sciences
- Law
- Sports and Recreation
- 14 more »
- « less
-
models that support operational analytics, strategic reporting, automation, and emerging AI-driven insights. This role is critical to enabling data-informed decisions across academic, administrative, and
-
Assistant Professor faculty position in the area of computational materials science with interests that may include, but are not limited to, quantum materials, multiscale modeling, and data-driven design of
-
and domain adaptation for data-scarce regions and integration of weather, mobility, and socioeconomic data for predictive modeling. Distributed infrastructure resource management, including data-driven
-
-based methods are particularly well-suited to bridging the molecular and experimental scales and will be central to this effort. The research will be performed in the Theory and Modelling group (https
-
-organ models; high-content functional screening systems; biomedical digital twins; computational modeling of living systems; AI-driven physiological and pathological modeling; high-performance computing
-
-heavy model updates, the proposed approach will use event-driven and sparse-update mechanisms so that learning updates are transmitted only when meaningful local changes occur. This will significantly
-
-impact resource that improves mechanistic drug profiling and informs model selection across cancer research and drug discovery. In line with our and Uni Basel values (https://www.unibas.ch/en/Research
-
improving and extending existing modeling frameworks such as the Large Basin Runoff Model (LBRM) and data-driven Artificial Intelligence (AI) approaches, including Long Short-Term Memory (LSTM) networks and
-
, and mineralogy Independent, self‑driven researcher with a strong problem‑solving mindset Proven team player, able to collaborate across multiple institutions Critical thinking to assess model
-
, gene editing, medicinal chemistry, and DNA-encoded library (DEL) technology, among others. For detailed information, please visit us at https://siais.shanghaitech.edu.cn/ . Join Our Institute: Faculty