Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Spain
- Norway
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Finland
- Ireland
- Luxembourg
- Switzerland
- China
- Canada
- Czech
- Estonia
- Austria
- Morocco
- United Arab Emirates
- Poland
- Romania
- Hong Kong
- Brazil
- Japan
- Andorra
- Macau
- Saudi Arabia
- Vietnam
- Barbados
- Bulgaria
- Iceland
- Latvia
- Lithuania
- Malta
- Slovenia
- 31 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Environment
- Business
- Law
- Linguistics
- Arts and Literature
- Electrical Engineering
- Humanities
- Psychology
- Physics
- Social Sciences
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
-
scientific data, model architectures, and training dynamics influence scientific predictions. You will join a vibrant research environment at TU/e at the intersection of AI, scientific computing, and
-
. Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making. Demonstrated experience designing and implementing ETL/ELT
-
, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
-
Actionable Data for Opioid Response in KY (RADOR-KY) project. This position will build data science solutions and predictive models for time series forecasting systems related to risk prediction, outcome
-
to predict nitrogen (N) and phosphorous (P) excretion, and this was published by Fox et al. (2004). Further, those predictions were refined and improved and partition N and P excretion between urine and feces
-
., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
-
predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
-
-funded project Predictive processing in naturalistic language comprehension through EEG and computational modeling, which is a collaboration between Dr. Brennan, and Dr. Edith Kaan at the University
-
bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how