Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- INESC TEC
- University of Bergen
- Simons Foundation/Flatiron Institute
- University of Oslo
- Harvard University
- UiT The Arctic University of Norway
- Carnegie Mellon University
- Nature Careers
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- KINGS COLLEGE LONDON
- Simons Foundation
- City University London
- Imperial College London
- King's College London
- Lawrence Berkeley National Laboratory
- University of Hertfordshire;
- University of New South Wales
- INESC ID
- Indiana University
- Institut national de la recherche scientifique (INRS)
- Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra
- Instituto Politécnico de Beja
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- NTNU - Norwegian University of Science and Technology
- Nanyang Technological University
- National University of Singapore
- Northeastern University
- Politécnico de Leiria
- Queen's University Belfast
- Simula Research Laboratory
- The University of British Columbia (UBC)
- UNIVERSITY OF HELSINKI
- UNIVERSITY OF SOUTHAMPTON
- UNIVERSITY OF SYDNEY
- UNIVERSITY OF WESTERN AUSTRALIA
- Universidade Nova de Lisboa
- Universidade de Coimbra
- University of Agder
- University of California
- University of Cincinnati
- University of Glasgow
- University of Helsinki
- University of Ljubljana
- University of South-Eastern Norway
- University of Southern Denmark
- University of Turku
- Zintellect
- 37 more »
- « less
-
Field
-
-efficient computing Developing mathematical modeling for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer
-
develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
-
architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
-
that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field
-
algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
-
or international conference. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Research and development of algorithms for analyzing signals acquired in real time by a system with integrated
-
suitable voltage and frequency control strategies, based on state-of-the-art research, and development of dispatch algorithms for the isolated microgrid, considering the coordinated control of generation
-
insurance, supported by INESC TEC. 2. OBJECTIVES: Study the state-of-the-art in space robotics, focusing on navigation, control, and gas propulsion systems.; • Develop navigation, detection, and localization
-
17172 (COMPETE2030-FEDER-00864900) co-funded by the ERDF - European Regional Development Fund through Innovation and Digital Transition Program - COMPETE 2030 under the scope of Portugal 2030 and by
-
OF THE WORK PROGRAMME AND TRAINING: 1) Development of workflows and algorithms to complement datasets of connected data spaces, to improve analysis results (forecasting, analysis of financial tools, predictive