Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- INESC ID
- UiT The Arctic University of Norway
- OsloMet
- University of Stavanger
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Universidade de Coimbra
- Instituto de Telecomunicações
- INESC TEC
- Instituto Superior Técnico
- Max Planck Institutes
- Nansen Environmental and Remote Sensing Center
- Nature Careers
- Umea University
- University of Oslo
- 4 more »
- « less
-
Field
-
30th April 2026 Languages English Norsk Bokmål English English PhD Fellow in Machine Learning Apply for this job See advertisement About us The Nansen Center is a Norwegian environmental research
-
Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
-
; - academic curriculum with background on the computer science and machine learning background; - previous research and professional experience on the scientific domains of the work. Additional Information
-
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 8 hours ago
. Preference will be given to candidates with aptitude for working in disaster risk management environments supported with GIS and Machine Learning, basic programming skills (e.g., Python, R, or similar
-
15 Apr 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application
-
experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, AI, software engineering, or security-related domains. Research track record and scientific
-
, wearable physiological sensing, and machine learning to uncover how factors like fatigue and cognitive workload impact technician performance. Join us to develop predictive models that predict human error
-
modelling, or modelling of physical/dynamical systems. familiarity with AI/machine learning/system identification techniques and their application to engineering problems. knowledge of digital twin concepts
-
while protecting data privacy. Unlike traditional centralized machine learning, where data must be collected and stored in a central server, FL allows multiple parties to collaboratively build a global
-
years with research duties exclusively,. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout