Sort by
Refine Your Search
-
, including biosolutions. The institute’s tasks are carried out in interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is
-
. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with correspondingly skilled
-
mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
-
to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic
-
, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or cheminformatics are advantages. The candidate must be able to work independently, but also participate in
-
with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
-
functional priors from billions of years of evolution; how to compress measurements with controlled mixtures of molecules; and how to align models of laboratory experiments with observational human biology
-
optimization. We are looking for a candidate who is motivated by both technical curiosity and making a real-world impact. Ideally, you: Have experience with AI models (e.g., graph neural networks, supervised
-
advancing your scientific career at a leading research institution. You will join two research groups at the DTU National Food Institute, Technical University of Denmark: “Food Production Engineering” and