Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- University of Oslo
- Monash University
- University of Nottingham
- Center for Drug Evaluation and Research (CDER)
- Centrale Supelec
- Centro de Engenharia Biológica da Universidade do Minho
- Curtin University
- Eindhoven University of Technology (TU/e)
- FCiências.ID
- Indiana University
- Institut de Físiques d'Altes Energies (IFAE)
- National Renewable Energy Laboratory NREL
- Nature Careers
- Palevoprim
- Technical University Of Denmark
- Technical University of Denmark
- Universitaet Muenster
- University of Birmingham
- University of California, San Francisco
- University of Glasgow
- University of Maryland, Baltimore
- 11 more »
- « less
-
Field
-
Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | 9 days ago
or adverse events in rare disease populations due to limited data and low event frequencies. Frequentist methods often lack sufficient power to detect safety signals in these scenarios. Bayesian methods offer
-
mechanisms to support detection and isolation when required. Research Objectives The successful PhD candidate will work on: Data-driven nonlinear control under uncertainty Developing control strategies based
-
Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework”. The primary objective of the T-PRESS consortium is to
-
to maintain high label efficiency in non-stationary environments, supported by reproducible benchmarks and principled evaluation protocols. Key Objectives O1: Drift-aware querying: Develop acquisition functions
-
entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
-
physics-based insights with data-driven methods—such as physics-informed neural networks, surrogate models and Bayesian optimisation—to explain formation behaviour, identify early indicators of cell
-
Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference and probabilistic
-
models) to test the emergence (initial radiation) and canalization of morphologies observed today throughout primate phylogenetic history, including fossil evidence. Objectives To implement a study of
-
area Software Engineering The objective of this project is to design automated approach to detect bugs in various software, e.g., compilers, data libraries and so on. The project may involve LLMs
-
features. Build and test pipelines for pose detection, object tracking, optical-flow analysis, and gaze–scene alignment, in collaboration with computer vision researchers. Analyze large multimodal datasets