PhD-Position in Bayesian statistics and machine learning at JMU Würzburg
The Data Science Chair at JMU Würzburg as a member of the Center for AI and Data Science (CAIDAS) and the Professorship of Inverse Problems at the Chair of Scientific Computing offer one
position for doctoral researchers (m/w/d)
in the area of machine learning.
The position will start as soon as possible and will be fixed term for an initial period of one year with the possibility of further extension for at least one more year. The position is full time and remuneration will be based on the Tarifvertrag für den öffentlichen Dienst der Länder (collective agreement for the public service of German federal states, TV-L). Candidates are expected to have a strong background at the interface of computer science and mathematics, with a specialization in machine learning or Bayesian statistics and interest in the project’s topic.
The project, HydrAS, has a strong focus on theoretical research. Here, you have the opportunity to work on the HypTrails method, which can be used to compare different hypotheses about user behavior by means of Bayesian statistics. HydrAS aims to extend this method with (semi-)automatic generation and testing of hypotheses as well as include more powerful statistical models like continuous time Markov chain models.
The successful candidate will jointly be supervised by Prof. Dr. Andreas Hotho (Computer Science, firstname.lastname@example.org ) and Prof. Dr. Frank Werner (Mathematics, email@example.com). You are welcome to contact us under these addresses for additional details.
Please send your application (letter of motivation, curriculum vitae, academic records) at your earliest convenience to firstname.lastname@example.org.
The University of Würzburg is an equal opportunity employer. As such, we explicitly encourage applications from qualified women. Severely handicapped applicants will be given preferential consideration in the case of broadly equal suitability, ability and professional achievements.
The closing date for applications is December 31st.
Further information on the Data Science Chair:
Further information on the Professorship of Inverse Problems: