Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- DAAD
- ;
- Curtin University
- Leibniz
- Technical University of Munich
- Susquehanna International Group
- University of Groningen
- Cranfield University
- Swedish University of Agricultural Sciences
- Technical University of Denmark
- Monash University
- Nord University
- University of Utah
- ; Newcastle University
- Ludwig-Maximilians-Universität München •
- Pennsylvania State University
- Forschungszentrum Jülich
- Rutgers University
- The University of Chicago
- University of Antwerp
- University of Bergen
- University of Göttingen •
- University of Nottingham
- Wageningen University and Research Center
- ; University of Nottingham
- Abertay University
- Duke University
- Ghent University
- IRTA
- Linköping University
- MASARYK UNIVERSITY
- Purdue University
- THE UNIVERSITY OF HONG KONG
- Umeå University
- University of Adelaide
- University of Bonn •
- University of Cambridge
- University of Liverpool
- University of Luxembourg
- University of Massachusetts Medical School
- University of Newcastle
- University of Oslo
- University of Oxford
- University of Southern Denmark
- VIB
- ; Swansea University
- ; University of Birmingham
- ; University of Exeter
- AALTO UNIVERSITY
- Aarhus University
- Baylor College of Medicine
- CNRS
- Carnegie Mellon University
- Cornell University
- Hannover Medical School •
- Humboldt-Universität zu Berlin •
- Imperial College London
- Institut Pasteur
- KINGS COLLEGE LONDON
- Kaiyuan International Mathematical Sciences Institute
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institutes
- NTNU - Norwegian University of Science and Technology
- Queensland University of Technology
- Radix Trading LLC
- SciLifeLab
- Sveriges lantbruksuniversitet
- The University of Iowa
- UNIVERSITY OF HELSINKI
- UiT The Arctic University of Norway
- University of California, Los Angeles
- University of Copenhagen
- University of Manchester
- University of Pennsylvania
- University of Sheffield
- University of Twente (UT)
- University of Tübingen
- University of Vienna
- Uppsala universitet
- Utrecht University
- Wageningen University & Research
- Wayne State University
- ; Coventry University Group
- ; Imperial College London
- ; King's College London
- ; St George's, University of London
- ; The University of Manchester
- ; UCL
- ; University of Bristol
- ; University of Cambridge
- ; University of Limerick
- ; University of Oxford
- ; University of Sheffield
- ; University of Stirling
- ; University of Surrey
- ; University of Warwick
- AIT Austrian Institute of Technology
- Aalborg University
- Babes-Bolyai University
- 90 more »
- « less
-
Field
-
, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
-
. Experience in working with large data sets, knowledge of statistics, and some programming expertise is essential. The project is based in ECEHH, at the University of Exeter’s Penryn Campus in Cornwall, and may
-
the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
-
analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
-
comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and mapping them onto phylogenetic trees Collaborating with a multidisciplinary team of biomechanists
-
on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
-
filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
-
informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world
-
organizing collective behaviour Analysing interspecific variation in swarming behaviour using comparative and statistical approaches Exploring evolutionary hypotheses by clustering behavioural traits and
-
synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project