Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Radboud University
- Eindhoven University of Technology (TU/e)
- Queensland University of Technology
- SciLifeLab
- University of Exeter
- University of Texas at El Paso
- Aalborg Universitet
- Aalborg University
- Fondazione Bruno Kessler
- Geological Survey of Denmark and Greenland (GEUS)
- Inria, the French national research institute for the digital sciences
- KU LEUVEN
- Luxembourg Institute of Science and Technology (LIST)
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- National Research Council Canada
- National University of Singapore
- Purdue University
- Technical University of Munich
- The University of Iowa
- Umeå University
- University of Cambridge;
- University of East Anglia
- University of Surrey
- University of Tübingen
- 17 more »
- « less
-
Field
-
, generate the behavioral data and brain samples that feed downstream imaging, atlas mapping, and ML/AI work. The NIH-funded Imaging & Behavioral Neuroscience (IBN) Core Facility supports both ends
-
well as engineering solutions for downstream processing. This position offers a unique opportunity to work at the interface of nanomedicine, molecular modeling, and process engineering, while contributing to the future
-
familiarity with downstream transcriptomic methods (e.g. RNA sequencing, RT-qPCR). Experience with live-cell fluorescence imaging, including confocal microscopy and the use of genetically encoded biosensors
-
in predictions derived from medical reports, and on integrating these uncertainties into downstream probabilistic time-to-event models. Applications will focus on prostate cancer, using large-scale
-
considered in the current models. whether there are common points in multiple models. This will identify potentially critical points for new models. identify upstream and downstream points not previously
-
, and downstream decisions, and to study how agentic reasoning can navigate trade-offs between interpretability, statistical reliability, and computational feasibility – and to develop principled criteria
-
considering both decision objectives and available resources. The central scientific aim of the PhD project is to establish formal links between uncertainty representations, risk measures, and downstream