Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Monash University
- Nature Careers
- ;
- CNRS
- Imperial College London
- KINGS COLLEGE LONDON
- University of Sheffield
- Nanyang Technological University
- University of Glasgow
- University of London
- University of Washington
- Zintellect
- ETH Zurich
- Forschungszentrum Jülich
- Heriot Watt University
- King Abdullah University of Science and Technology
- King's College London
- Montana State University
- NIST
- Purdue University
- Stony Brook University
- Technical University of Munich
- UNIVERSITY OF VIENNA
- University of Bergen
- University of Bristol
- University of Michigan
- University of Minnesota
- University of Toronto
- University of Vienna
- CEA
- California State University, Fullerton
- Columbia University
- Dalhousie University
- Duke University
- Institut Pasteur
- Northeastern University
- Oak Ridge National Laboratory
- Rice University
- SUNY Polytechnic Institute
- SUNY University at Buffalo
- SciLifeLab
- The Ohio State University
- The University of Queensland
- UNIVERSITY OF HELSINKI
- University of Adelaide
- University of Birmingham
- University of Bristol;
- University of Florida
- University of Manchester
- University of Miami
- University of Oslo
- Utrecht University
- ; Newcastle University
- ; Swansea University
- ; University of Southampton
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Aarhus University
- Argonne
- Arizona State University
- Aston University
- Australian National University
- Beijing Normal-Hong Kong Baptist University (BNBU)
- Brookhaven Lab
- Brookhaven National Laboratory
- California State University
- Cardiff University
- Case Western Reserve University
- Centro de Investigación en Matemáticas
- DAAD
- Dartmouth College
- Delft University of Technology
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- FCiências.ID
- FLINDERS UNIVERSITY
- Flinders University
- Fraunhofer-Gesellschaft
- Freenome
- French National Research Institute for Sustainable Development
- Friedrich Schiller University Jena
- GFZ Helmholtz Centre for Geosciences
- Georgetown University
- Harbin Engineering University
- Japan Agency for Marine-Earth Science and Technology
- Johns Hopkins University
- King's College London;
- La Trobe University
- London School of Hygiene & Tropical Medicine;
- Ludwig-Maximilians-Universität München •
- Maastricht University (UM)
- Malopolska Centre of Biotechnology
- Massachusetts Institute of Technology
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institutes
- National Aeronautics and Space Administration (NASA)
- National Centre for Nuclear Research
- New York University
- North Carolina State University
- Rutgers University
- Syracuse University
- 90 more »
- « less
-
Field
-
to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
-
uncertainty. Relevant areas include interpretable probabilistic, causal, Bayesian, and knowledge-based networks. While expertise in electromagnetics is not essential, applicants must be willing to broaden
-
associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
-
including, but not limited to: Bayesian statistics, computational statistics, inverse problems, numerical analysis, probability, statistical machine learning, stochastic analysis, and uncertainty
-
Probability, Regression Analysis, Multivariate Analysis, Categorical Data Analysis, Optimization, Time Series Analysis, Survival Analysis, Actuarial mathematics, Data Mining and Bayesian Statistics are welcome
-
of biofouling processes in marine environments. This role will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how
-
for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques); analyzing what is required (e.g., choice
-
of different forms of human, Training in radiocarbon dating and its application to archaeology, pretreatment chemistry, palaeoproteomics and the Bayesian modeling of radiocarbon dates will be given, but prior
-
features to behavior using GLMMs/Bayesian models; conduct sensitivity and robustness checks. * Method validation: benchmark alternative pipelines (filters, burst detectors, forward/inverse models); perform
-
Centre (NCN). The Principal Investigator is Dr. Eng. Piotr Kopka, email: Piotr.Kopka@ncbj.gov.pl Project description: The project aims to develop a new class of inverse Bayesian models called STE-EU-SCALE