Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
in humans and in animal models. Environmental factors have been reported to predict the risks of developing SUDs too. For instance, epidemiological data have shown that impoverished social environments
-
in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
-
interfaces and driver modelling Implementation of control algorithms in mechatronic systems Experimental design and statistical methods Vehicle testing and test methods involving human test subjects What you
-
of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
-
components in time and space, from single molecules to native tissue environments. The project The industrial PhD student will develop AI and machine learning models to predict drug metabolism, a critical area
-
-technology/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Sustainability assessment and biophysical modelling Research subject: Technology
-
, flexible and adaptable distributed system of systems. Example of specific problems are: -Information interoperability supported by ontologies. -Unified data models for operational environmental impact -SOA
-
environmental factors. Findings will be further explored through bioinformatic methods. Other techniques may include machine learning and mathematical modeling. Additional tasks within the research group may also
-
environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with
-
transformation of SMEs through cutting-edge digital innovation and circular business models. Your work will help empower companies to decarbonize, minimize waste, and build resilient, future-proof value chains