Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Munich
- Cranfield University
- Technical University of Denmark
- ;
- Forschungszentrum Jülich
- Nature Careers
- Curtin University
- DAAD
- Monash University
- University of Southern Denmark
- Chalmers University of Technology
- Ghent University
- University of Groningen
- NTNU - Norwegian University of Science and Technology
- Umeå University
- University of Adelaide
- Vrije Universiteit Brussel
- ; Newcastle University
- ; Swansea University
- ; The University of Manchester
- Imperial College London
- Leiden University
- Radboud University
- University of Cambridge
- University of Nottingham
- ; Technical University of Denmark
- ; University of Cambridge
- ; University of Exeter
- ; University of Leeds
- Aalborg University
- Aarhus University
- Leibniz
- Linköping University
- Susquehanna International Group
- University of British Columbia
- University of Copenhagen
- University of Southern Queensland
- University of Twente
- Utrecht University
- ; Brunel University London
- ; University of Birmingham
- ; University of Bristol
- ; University of East Anglia
- ; University of Oxford
- ; University of Sheffield
- ; University of Southampton
- ; University of Surrey
- CNRS
- CSIRO
- Deutsches Elektronen-Synchrotron DESY •
- Erasmus University Rotterdam
- Harper Adams University
- Helmholtz-Zentrum Geesthacht
- Institut Pasteur
- Leibniz-Institute for Plant Genetics and Crop Plant Research
- Lulea University of Technology
- Max Planck Institute for Molecular Genetics •
- Max Planck Institutes
- McGill University
- Purdue University
- Queensland University of Technology
- Saarland University •
- SciLifeLab
- TU Dresden
- Technical University of Denmark;
- The University of Alabama
- Trinity College Dublin
- University of Alabama, Tuscaloosa
- University of Antwerp
- University of Bern
- University of Bremen •
- University of Bristol;
- University of Glasgow
- University of Luxembourg
- University of Minnesota
- University of Minnesota Twin Cities
- University of Nebraska–Lincoln
- University of Nottingham;
- University of Oslo
- University of Potsdam •
- University of Texas at Austin
- Uppsala University
- Wageningen University and Research Center
- 73 more »
- « less
-
Field
-
variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
-
of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
-
Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
-
and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
-
formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
-
play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
-
quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
-
, or spatial relationships of objects—and to indicate when it is unsure about its input. Key expected outcomes include the creation of monitoring algorithms that identify early signs of performance issues, and
-
specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling
-
experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly