Aufgabe:
* Plan, administer and deliver classes of a total of approximately 3.5 teaching contact hours per week * Collaborate on research regarding approximate sampling of distributions, analysis of Markov chain Monte Carlo methods, Bayesian inference and algorithmic design in general on the borderline between Machine Learning and mathematics * Organise and support conferences/sessions/workshops and grant proposalsQualifikation:
* Must have a master's degree and a strong background in mathematics, statistics, Machine Learning or a related field * Strong theoretical background in at least one of the following areas: o Stochastic processes o Markov chain Monte Carlo o Quasi-Monte Carlo o Bayesian inferenceWeitere Angebote in den Bereichen:
