Sort by
Refine Your Search
-
, their achievements and productivity to the success of the whole institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Robotics offers a full-time
-
breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
-
quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent spoken and written English and the
-
and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
-
challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
-
. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
-
chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive
-
or equivalent degree in Biology, Immunology, Biochemistry or a related discipline. Alternative: MD with a strong interest in basic research Enthusiasm for joining basic research with clinically relevant issues
-
ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
-
less than eight semesters, three references are required; please use the official DAAD template [doc-Datei] and ask your professors to email the confidential document to the GSPoL. Step 2: personal