Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Radboud University
- University of Oslo
- ; Max Planck Institute for Psycholinguistics
- ; University of Exeter
- ; University of Sussex
- ; University of Warwick
- Aalborg University
- Aston University
- Chalmers University of Technology
- Delft University of Technology (TU Delft)
- Institut Pasteur
- Maastricht University (UM)
- Nature Careers
- Swedish University of Agricultural Sciences
- Technical University Of Denmark
- Technical University of Denmark
- Technical University of Munich
- Utrecht University
- 8 more »
- « less
-
Field
-
now Are you interested in designing and analysing algorithms for Bayesian networks that contribute to traceability, source attribution, and justification in clinical decision support systems? Do you
-
systems (CDSSs), so that their use in the clinic can be subject to rigorous quality control and certification. In this position, you will work on exploring synergies between Bayesian networks and AutoML
-
architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning
-
candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of molecular data in cancer genomics. The position is connected
-
”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
-
this, the impact of the heterogeneity in the structure of the individuals contact network on disease transmission will be investigated. The candidate will gain experience in a range of mathematical and computational
-
. Opportunities to participate in conferences, symposia, and networking events to share and enhance your research. Your role will be pivotal in driving AI innovation and contributing to a transformative approach to
-
the SOFA framework to model the larva’s body dynamics. Create a mesh model of the larva with the main organs required for simulation and develop plugins to control muscle and body properties. Modelling
-
infrastructure development. However, we lack consensus methods for assessing generative AI’s compliance with GDPR. The purpose of the PhD stipend is to build Bayesian metrics for privacy-preserving AI (e.g
-
and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits