Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Forschungszentrum Jülich
- Nature Careers
- Technical University of Munich
- Curtin University
- DAAD
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- ETH Zürich
- University of Luxembourg
- CNRS
- Cranfield University
- Eindhoven University of Technology (TU/e)
- KINGS COLLEGE LONDON
- Norwegian University of Life Sciences (NMBU)
- Technical University of Denmark
- University of Southern Denmark
- University of Twente (UT)
- Delft University of Technology (TU Delft); Delft
- La Trobe University
- Loughborough University
- Lunds universitet
- NTNU - Norwegian University of Science and Technology
- UNIVERSIDAD POLITECNICA DE MADRID
- Université Laval
- Uppsala universitet
- ;
- Aalborg University
- Academic Europe
- Agricultural university - Plovdiv, Bulgaria
- Amsterdam UMC
- Ariel University
- Arts et Métiers Institute of Technology (ENSAM)
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Brookhaven Lab
- Brookhaven National Laboratory
- COFAC
- Centre for Genomic Regulation
- Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy
- Cornell University
- Delft University of Technology (TU Delft); 3 Oct ’25 published
- Deutsches Elektronen-Synchrotron DESY •
- Dublin City University
- Ecole Normale Supérieure
- Edmund Mach Foundation
- Elestor BV
- Erasmus MC (University Medical Center Rotterdam)
- Erasmus MC (University Medical Center Rotterdam); Rotterdam
- FCT NOVA - UNIDEMI
- Fraunhofer-Gesellschaft
- Ghent University
- Graz University of Technology
- Hannover Medical School •
- Human Technopole
- IMEC
- IRTA
- Itä-Suomen yliopisto
- Jagiellonian University
- KU LEUVEN
- King's College London
- Leibniz
- Linköpings universitet
- Ludwig-Maximilians-Universität München •
- Maastricht University (UM); Maastricht
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute of Biochemistry, Martinsried
- McGill University
- Monash University
- Mälardalen University
- NTNU Norwegian University of Science and Technology
- New York University
- Oxford Brookes University
- Queensland University of Technology
- Radboud University
- School of Business, Society and Engineering
- TU Dresden
- Tallinn University of Technology
- Technische Universität Berlin •
- The University of Alabama
- The University of Newcastle
- UCL
- Umeå University
- Umeå universitet
- Universidade de Coimbra
- Universidade de Vigo
- University Medical Centre Groningen (UMCG)
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Amsterdam
- University of Basel
- University of California, Los Angeles
- University of Cambridge
- University of Cambridge;
- University of East Anglia
- University of Essex
- University of Lund
- University of Minnesota
- University of Sheffield
- University of Twente
- University of Twente (UT); Enschede
- 90 more »
- « less
-
Field
-
sciences and artificial intelligence, and translate your findings to improve human health? Are you excited to develop and use machine learning approaches to gain new understanding of the molecular physiology
-
Course location Hamburg Description/content The Cluster of Excellence "CUI: Advanced Imaging of Matter", which is funded by the German federal and state governments, combines projects in physics
-
mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
-
. The underwater acoustic communication technologies will help. The school is focusing on research in AI/machine learning and signal processing which are the research areas in this proposed project. We have
-
structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
-
publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
-
Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
-
, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
-
technologies, social structures, and networks. Effective C2 organisational systems are critical not only to military settings, but also to the operation of many civil domains, including emergency response
-
Physics , Living Systems , Machine Learning , many-body quantum geometry; altermagnetism; cavity quantum science; quantum non-equilibrium processes; Casimir physics , Material Science , Materials Science