Faculty of Mathematics and Natural Sciences – Department of Mathematics

Job description:

• scientific services in research within the DFG project “Operator Learning for Optimal Control: Approximation and Statistical Theory”, in particular in the field of Operator Learning
• development of theoretical foundations for statistical learning of nonlinear operators
• applications include parameter-to-solution maps in parameter dependent partial differential equations (PDEs)

Requirements:

• completed scientific university degree in mathematics or related fields
• strong background in at least one of the following fields: statistics, PDEs, probability theory, numerical analysis or optimization
• highly motivated to conduct theoretical and applied research in scientific machine learning and related mathematical fields
• basic proficiency in programming (e.g. in MATLAB/Python)
• good command of written and spoken English

Please send your application referencing the job ID DR/111/24 to Humboldt-Universität zu Berlin, Faculty of Mathematics and Natural Sciences, Department of Mathematics, Prof. Dr. Sven Wang (located: Rudower Chaussee 25, 12489 Berlin), Unter den Linden 6, 10099 Berlin or preferably via e-mail as a single PDF file to sven.wang@hu-berlin.de.

The Humboldt-Universität zu Berlin is seeking to increase the proportion of women in research and teaching, and specifically encourages qualified female scholars to apply. Severely disabled applicants with equivalent qualifications will be given preferential con- sideration. People with an immigration history are specifically encouraged to apply. Since we will not return your documents, please submit copies in the application only.

Information pursuant to Art. 12, 13 DSGVO on the processing of personal data at Humboldt Universität within the framework of job advertisements can be found on our Website: https://hu.berlin/DSGVO.

Please visit our website www.hu-berlin.de/stellenangebote, which gives you access to the legally binding German version.