Open positions

Currently there are several positions to be filled.

Postdoctoral researcher in Phylomilia project (m/f/d; E13 TV-L)

Applications are invited for the post of a

postdoctoral researcher (m/f/d, E13 TV-L)

in the Linguistics Department, working with Prof. Gerhard Jäger. This vacancy is connected to the award of funding of a project Phylomilia – Phylogenetic linguistic inference from acoustic speech data, for the period 2024-27 by the Volkswagen Foundation (also see here). The project will be based at the University of Tübingen. The principal activity of the postdoctoral researcher will be to undertake research in deep-learning based automatic speech recognition and in phylogenetic inference. A solid background, including a PhD in a relevant discipline, in modern statistical and machine learning methods in NLP is required.

The Linguistics Department (http://www.sfs.uni-tuebingen.de/) offers a stimulating interdisciplinary research environment.

The salary is figured according to the union contract named TV-L, E13, depending on professional experience.

The period of employment will be for 3 years.

Applications should include CV, an outline of research experience, as well as names and addresses of up to three references. Applications should be sent by email to the address below. The position will be filled as soon as possible. Deadline for applications is August 31, 2024.

Disabled applicants will be preferred if they have the same qualifications as non-disabled applicants. The University of Tübingen strives to increase the proportion of women in research and teaching, and therefore encourages qualified female scientists to apply.

Please send your application electronically as a single pdf file to gerhard.jaegerspam prevention@uni-tuebingen.de.

The contract will be made by the central administration of the university.

Several PhD positions in Machine Learning Based Data Anaysis of Scattering and Diffraction Data

The Schreiber Group at the University of Tübingen works on the physics of molecular and biological materials using X-ray and neutron scattering. A specialised sub-group is dedicated machine learning based data analysis of scattering and diffraction data. Currently we have several

PhD positions (m/f/d)

available. Candidates with experience or interest in neural networks and machine learning strategies to analyse scattering are especially encouraged to apply.

You should have good communication skills, attention to detail, and flexibility to work both independently as well as in a team. You should hold either a diploma/master degree in physics, physical chemistry, material science or have a background in computer science.

You will be part of challenging interdisciplinary projects that are integrated into major national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. We offer well-equipped laboratories, a highly collaborative international environment and affiliation with the Cluster of Excellence "Machine Learning: New Perspectives for Science" funded by the DFG and hosted at the University Tübingen. You will receive excellent training and for all our projects we offer the opportunity to perform research at international large-scale facilities (such as synchrotrons and neutron sources).  Details on our research as well as publications and background information can be found at http://www.soft-matter.uni-tuebingen.de/machine_learning_XRR.html and http://www.soft-matter.uni-tuebingen.de/machine_learning_GIWAXS.html

The University of Tübingen has ~ 28,000 students and more than 500 years of academic tradition. It has national excellence status as is ranked in the top 100 universities worldwide. You will benefit from a variety of training opportunities and language courses as well as the university’s graduate academy. See also https://uni-tuebingen.de/en/excellence-strategy.

Applications should include a cover letter describing research interests, achievements, motivation and capabilities; curriculum vitae; academic certificates; names and email addresses of two professional references (e.g., current or previous research advisors). The opening will remain valid until the position is filled.

The positions are available immediately. Salary will be determined according to the German collective wage agreement in public service. Please send your application within one PDF file to softmatterspam prevention@ifap.uni-tuebingen.de

The University aims to increase the proportion of women in research and teaching and therefore urges suitable qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Severely disabled persons with equal aptitude will be given preferential consideration.