Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Denmark
- Nature Careers
- Cranfield University
- CNRS
- NTNU - Norwegian University of Science and Technology
- Susquehanna International Group
- DAAD
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Forschungszentrum Jülich
- Leibniz
- UNIVERSITY OF HELSINKI
- Vrije Universiteit Brussel
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e); Eindhoven
- Leiden University
- Maastricht University (UM)
- Maastricht University (UM); Maastricht
- Mälardalen University
- NTNU Norwegian University of Science and Technology
- Tallinn University of Technology
- University of Adelaide
- University of Bergen
- University of Groningen
- University of Nottingham
- University of Sheffield
- University of Twente (UT)
- VIB
- ; Brunel University London
- ; Newcastle University
- ; Swansea University
- ; The University of Manchester
- ; University of Exeter
- Aarhus University
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Arts et Métiers Institute of Technology (ENSAM)
- Centre for Genomic Regulation
- Delft University of Technology (TU Delft); Delft
- Duke University
- Elestor BV
- Erasmus MC (University Medical Center Rotterdam)
- FCT NOVA - UNIDEMI
- Ghent University
- Harper Adams University
- ICN2
- IRTA
- Institutionen för biomedicinsk vetenskap
- Instituto de Telecomunicações
- King's College London;
- Leiden University; Leiden
- Linköping University
- Ludwig-Maximilians-Universität München •
- Maastricht University (UM); 3 Oct ’25 published
- Medizinische Universitaet Wien
- Monash University
- National Centre for Nuclear Research
- Norwegian Meteorological Institute
- Radboud University Medical Center (Radboudumc)
- SINTEF
- School of Business, Society and Engineering
- SciLifeLab
- Technical University of Munich
- UCT Prague
- Universiteit van Amsterdam
- University College Dublin
- University Medical Center Utrecht (UMC Utrecht)
- University Medical Center Utrecht (UMC Utrecht); yesterday published
- University Medical Centre Groningen (UMCG)
- University Medical Centre Groningen (UMCG); Groningen
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); yesterday published
- University of Birmingham
- University of California Irvine
- University of Copenhagen
- University of Nottingham;
- University of Paris-Saclay
- University of Sheffield;
- Université Paris-Saclay (UPS)
- Université Paris-Saclay GS Mathématiques
- Uppsala universitet
- Wageningen University & Research
- Wageningen University and Research Center
- 72 more »
- « less
-
Field
-
parameters that have been learned from data. For instance, why does a machine learning model predict that it is unsafe to discharge a certain patient from the intensive care? Or which characteristics make a
-
years, practitioners and researchers have realized that predictions made by machine learning models should be transparent and intelligible. Although explainable AI methods can shed some light on the inner
-
, computational modelling, and machine learning, and is well-suited for candidates eager to develop computational frameworks for next-generation structural dynamics and nanomechanical technologies. The vacant
-
biopsies and develop and validate predictive models that support and enhance personalized care. Your tasks include: Designing and conducting scientific research, with a focus on machine-learning based
-
machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology, clustering, and diagnostics of cardiovascular diseases in critically ill patients
-
for uncovering nonlinearities and dissipation mechanisms, and design strategies for exploiting them. The project sits at the interface of nonlinear mechanics, computational modelling, and machine learning, and is
-
markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine
-
at cell membranes; Apply machine-learning models trained on simulation data to study how lipid composition and genetic variation influence the conformational and phase properties of membrane-associated
-
incomprehensible model parameters that have been learned from data. For instance, why does a machine learning model predict that it is unsafe to discharge a certain patient from the intensive care? Or which
-
, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine