Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Monash University
- Imperial College London
- ;
- CNRS
- KINGS COLLEGE LONDON
- University of Glasgow
- Columbia University
- ETH Zurich
- Forschungszentrum Jülich
- Heriot Watt University
- Institut Pasteur
- King's College London
- Nature Careers
- Rice University
- SUNY University at Buffalo
- UNIVERSITY OF HELSINKI
- University of Manchester
- University of Oslo
- Utrecht University
- ; University of Southampton
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Argonne
- Arizona State University
- Aston University
- Australian National University
- Binghamton University
- CEA
- Dalhousie University
- ETH Zürich
- FCiências.ID
- Freenome
- Johns Hopkins University
- King's College London;
- NIST
- New York University
- North Carolina State University
- Purdue University
- Syracuse University
- Technical University of Denmark
- The University of Arizona
- UCL;
- University of Adelaide
- University of California, Los Angeles
- University of Colorado
- University of Florida
- University of London
- University of Massachusetts
- University of Miami
- University of Michigan
- University of South Carolina
- University of Sydney
- University of Texas at Arlington
- University of Warsaw
- University of Warwick
- Université d'Orléans
- Utrecht University; Utrecht
- 46 more »
- « less
-
Field
-
high-dimensional neural data. Approaches used include neural network-based approaches, Bayesian inference, and more Assisting with the oversight of day-to-day functions of the lab and shared lab spaces
-
AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 20 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
-
(for example, R, Python, or Matlab). Experience with graph modeling, Bayesian statistics, or causal inference is a plus. The candidate will join an integrated team of computational scientists, molecular
-
Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 13 hours ago
Python programming. Experience guiding trainees in bioinformatics skills. Advanced knowledge of phylogenomic analyses and the use of site-profile mixture models in a Bayesian and Maximum likelihood context
-
experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
-
techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
-
developing and testing the computational mechanisms of social inference, although will have plenty of scope, and will be encouraged, to develop and expand their own research interests. The postholder will work
-
diagnosis of psychosis. The postdoctoral researcher will lead a research program focused on developing and testing the computational mechanisms of social inference, although will have plenty of scope, and
-
tenured/tenure-track faculty and nine full-time instructors. Current research areas of the faculty include survival and reliability analysis, Bayesian statistics, latent variable methods, item response
-
spans from advanced theoretical and methodological Statistics (classical and Bayesian) to diverse applications, allowing for comprehensive research approaches. Our members work on Design of Experiments