Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- UNIVERSITY OF SOUTHAMPTON
- University of Oslo
- Aalborg University
- CNRS
- Indiana University
- Montana State University
- National University of Singapore
- Nature Careers
- University of Amsterdam (UvA)
- Aalborg Universitet
- Cornell University
- Inria, the French national research institute for the digital sciences
- Institut de Físiques d'Altes Energies (IFAE)
- Johns Hopkins University
- KTH Royal Institute of Technology
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology (MIT)
- Max Planck Institute for Physics, Garching
- Newcastle University;
- Queen's University
- RIKEN
- Technical University of Denmark
- The University of Southampton
- UNIVERSITY OF HELSINKI
- Universidad Politécnica de Madrid
- University of Amsterdam (UvA); Published yesterday
- University of Amsterdam (UvA); yesterday published
- University of Bristol
- University of Bristol;
- University of Leeds
- University of Leeds;
- University of London
- University of Manchester
- University of Massachusetts Medical School
- University of Michigan
- University of Minnesota
- University of Oxford
- University of Southampton;
- 28 more »
- « less
-
Field
-
for approximate inference, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. It comprises Jan-Willem van de Meent, who
-
on the following activities related to Bayesian inference in factorial designs: Construction and elicitation of informed prior distributions; Critical assessment of default prior distributions; Organizing a many
-
Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
for individuals that are interested in pursuing a PhD in economics or finance. The chosen candidate will also gain valuable experience in the application of machine learning and Bayesian inference methods
-
-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department Contact for Questions Songhu Wang (sw121@iu.edu) Additional
-
communication and collaboration skills Preferred: Experience with simulation-based inference and Bayesian methods Familiarity with cosmological simulations or observational cosmology ML architecture design and
-
, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. It comprises Jan-Willem van de Meent, who serves as director, Max
-
following areas: Probabilistic or Bayesian Machine Learning Variational Inference, Ensemble, or Diffusion Models Spatio-Temporal or Sequential Modelling Graph Neural Networks Deep Learning and Uncertainty
-
/ Statistics , Applied Mathematics , Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning , Social Sciences , Biomedical Informatics , Causal Inference , Computational Social
-
employment. Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric methods” funded by the Research Council
-
to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field