Sort by
Refine Your Search
-
personal sphere of influence: We are seeking a PhD candidate to join the Biochemical Network Analysis group , led by Jürgen Zanghellini . The team focuses on mathematical modeling, artificial intelligence
-
using deep learning methods. The focus of our research is in the area of natural language processing with deep learning methods, especially large language models. This is a limited term position for 3
-
using deep learning methods. The focus of our research is in the area of natural language processing with deep learning methods, especially large language models. This is a limited term position for 3
-
detailed dynamical models of galaxies and stellar clusters to infer the distribution of luminous and dark matter as well as to uncover the formation history of these stellar systems. Ready to be part of our
-
models. Strong expertise and state-of-the-art instrumentation for preclinical development of novel anticancer drugs are provided by this team. The contract duration is 3 years with a preliminary limitation
-
You become an active team member of the “Applied Mathematics and Modeling” research group. Interdisciplinary collaboration: o You participate in international scientific collaborations, as well as in
-
% of their graduating classes) have a strong quantitative background have an interest in acquiring methodological skills in areas such as formal (mathematical) modelling and/or (quantitative) empirical testing
-
experienced programmer, preferably using the Python programming language. Experience modeling and solving vehicle routing problems involving variable travel durations is a plus. Experience modeling and solving
-
on the effects of nutrition and aging-related alterations of the gut-liver-axis and inflammatory processes in different model organisms (e.g. mice), but also in humans. Participation in paper writing and
-
of Vienna, investigating the complex drivers of landslide risk in rapidly urbanising tropical cities. The project will develop a hybrid modelling framework combining process-based and statistical methods