Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- INESC TEC
- Delft University of Technology (TU Delft)
- Inria, the French national research institute for the digital sciences
- KU LEUVEN
- NTNU Norwegian University of Science and Technology
- CNRS
- Technical University of Munich
- Universidade de Coimbra
- Eindhoven University of Technology (TU/e)
- INESC ID
- BI Norwegian Business School
- FEUP
- Fondazione Bruno Kessler
- Graz University of Technology
- Instituto Politécnico de Bragança
- Instituto Superior Técnico
- Leiden University
- Princeton University
- Utrecht University
- Aalborg Universitet
- Aalborg University
- Ludwig-Maximilians-Universität München •
- RPTU University Kaiserslautern-Landau •
- Radboud University Medical Center (Radboudumc)
- UNIVERSITATEA DIN CRAIOVA
- University of Basel
- University of Göttingen •
- University of Innsbruck
- University of Primorska
- University of Twente (UT)
- University of Washington
- Wageningen University & Research
- ARCNL
- Abertay University
- Adam Mickiewicz University
- Agencia Estatal Consejo Superior de Investigaciones Científicas
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- CMU Portugal Program - FCT
- COFUND QuanG
- Clover Park Technical College
- Deutsches Elektronen-Synchrotron DESY •
- Foundation for Research and Technology-Hellas
- GFZ Helmholtz-Zentrum für Geoforschung
- Grenoble INP - Institute of Engineering
- Hannover Medical School •
- IDAEA-CSIC
- IMDEA Networks Institute
- INTRACOM SA TELECOM SOLUTIONS
- Instituto de Sistemas e Robótica (ISR)
- Karlsruhe Institute of Technology •
- Loyola University
- Maastricht University (UM)
- Max Planck Institute for Biogeochemistry •
- Max Planck Institute for Meteorology •
- Max Planck Institute for the Study of Societies •
- Monash University
- National Research Council Canada
- Newcastle University
- Oslo University Hospital
- Radboud University
- Saarland University •
- SciLifeLab
- Sofia University "St. Kliment Ohridski"
- TU Delft
- Technical University Of Denmark
- Technische Universität Berlin •
- Technische Universität München
- The Chinese University of Hong Kong
- Trinity College Dublin
- UNINOVA - Instituto de Desenvolvimento de Novas Tecnologias
- Universidade Europeia
- University of Amsterdam (UvA)
- University of Aveiro
- University of Bamberg •
- University of Birmingham
- University of Borås
- University of Bremen •
- University of California
- University of Hamburg •
- University of Kentucky
- University of Münster •
- University of Nottingham
- University of Plymouth
- University of Potsdam •
- University of Tübingen •
- University of Zurich
- Virginia Community College
- Vrije Universiteit Amsterdam (VU)
- Youngstown State University
- Zintellect
- 80 more »
- « less
-
Field
-
and FCT code. 2023.18225.ICDT and e DOI https://doi.org/10.54499/2023.18255.ICDT , funded by COMPETE 2030 by Portugal 2030, and by the European Union financial support from national funds/OE through
-
organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
-
machine learning or computer vision models Technical competencies in one or more of the following: bio-digital systems, biodesign, applied machine learning, computer vision, computational biology, and/or
-
: i) Develop computer vision systems in the context of agriculture; ii) Develop computational systems iii) Promote the dissemination and exploitation of the results generated in the project. 4
-
interest?If so, we look forward to receiving your application by 6th October 2026. Please use our online application form only.Required documents: CV, including list of computer skills and programming
-
27 Sep 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
-
of the energy transition”, reference CETP/0003/2022, funded “Exclusively by National Funds through FCT, I.P. (CETP/0003/2022)”, under the following conditions: 1. Scientific Area: Computer Engineering 2
-
and opportunities as they arise and helping organisations to look ahead and shape our digital future. SCEBE works across a spectrum of fields of computer technology including smart sensors & networks
-
, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
-
proficiency in coding, knowledge of GIS environments and point cloud processing, strong interest in heritage scenarios as well as a collaborative attitude for interdisciplinary work between computer scientists