Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- University of Oslo
- Aalborg University
- Amsterdam UMC
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- Radboud University
- Radix Trading LLC
- SciLifeLab
- University of Amsterdam (UvA)
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- IMDEA Networks Institute
- Inria, the French national research institute for the digital sciences
- International PhD Programme (IPP) Mainz
- Murdoch University
- Queensland University of Technology
- Technical University of Denmark
- Technical University of Munich
- University of Birmingham
- University of Bristol
- University of Cambridge
- University of Exeter
- University of Luxembourg
- University of Nottingham
- Wageningen University & Research
- 16 more »
- « less
-
Field
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description We invite applications for a three-year PhD Research Fellowship in probabilistic machine learning and
-
UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
-
English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We invite applications for a three-year PhD Research Fellowship in
-
on “Machine Learning for Probabilistic Modelling” with Dr Edward Gillman and Professor Juan P. Garrahan as supervisors. Funding Fully and directly funded for this project only. Full tuition fee waiver p.a
-
learning, AI, cognitive science, uncertainty quantification, probabilistic methods are encouraged to apply. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend
-
for candidates with a background in or demonstrated ability to learn about: Bayesian methods, probabilistic machine learning or inverse modelling. Prospective applicants are encouraged to direct informal inquiries
-
develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
-
. In this way, flood impacts can also be described probabilistically and later added to the model of Pillar 1; Translating the current scenario sets into future climate states (using climate scenario as
-
defences, and account for uncertainty in breach growth. In this way, flood impacts can also be described probabilistically and later added to the model of Pillar 1; Translating the current scenario sets
-
cardiovascular disease. A possible direction for the work is the development of probabilistic graphical models that represent proteins as latent causal drivers of disease, while treating other omics layers as