301 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" research jobs in Sweden
Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- Chalmers University of Technology
- Lunds universitet
- University of Lund
- Karolinska Institutet (KI)
- Swedish University of Agricultural Sciences
- Umeå universitet stipendiemodul
- Umeå University
- Uppsala universitet
- Nature Careers
- Linköping University
- KTH Royal Institute of Technology
- SciLifeLab
- Lulea University of Technology
- Stockholms universitet
- Sveriges Lantbruksuniversitet
- Umeå universitet
- Luleå University of Technology
- University of Borås
- Luleå tekniska universitet
- Örebro University
- Blekinge Institute of Technology
- IFM, Linköping University
- Jönköping University
- KTH
- Karlstad University
- Lund University
- Mälardalen University
- SLU
- European Magnetism Association EMA
- Faculty of Culture and Society
- Göteborg Universitet
- Göteborgs universitet, Department of Marine Sciences
- Högskolan Väst
- Institutionen för akvatiska resurser
- Institutionen för växtskyddsbiologi
- Linnaeus University
- Linneuniversitetet
- Luleå tekniska universitet/Luleå University of Technology
- Luleå university of technology
- Stockholm University
- The Swedish University of Agricultural Sciences (SLU)
- Umeå Plant Science Center
- University of Gothenburg
- 33 more »
- « less
-
Field
-
well as in urban areas. See also: https://www.slu.se/en/about-slu/organisation/departments/ecology/ About the position The researcher will work in the field (in southern Sweden), with statistical analyses, and
-
fundamental questions about soil health in agricultural cropping systems and advance your research career in a leading international research environment. The position is part of the EU project MultiSoil (https
-
Description of the workplace The position will be placed at the division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an
-
stochastic dynamics for shape change. A further aspect of the project is learning and calibrating these models from data using data-driven inference methods. Who we are looking for Required qualifications A
-
science, machine learning, automated systems, or a closely related field Have experience working with ruminants Have experience in precision agriculture and/or precision livestock farming Have experience
-
technologies. The OEM group is part of the Laboratory of Organic Electronics (LOE) (https://liu.se/LOE ), an internationally renowned research environment comprising more than 150 researchers from diverse
-
statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
-
multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
-
testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
-
–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral