Department of Computer Science

Department of Computer Science - News

23.08.2021

Group Leader E14 TV-L, 100%

The new interdisciplinary research group Medical Data Privacy and Privacy-preserving Machine Learning on healthcare data (MDPPML) at Prof. Dr. Nico Pfeifer’s Chair for Methods in Medical Informatics, Department of Computer Science, is currently looking for a GROUP LEADER (f/m/d, E14 TV-L, 100%) starting as soon as possible. The initial fixed-term contract will have an end date of 31/03/2024 with possible extension.

Responsibilities
Your tasks will include:
- Design, development, and analysis of efficient privacy enhancing technologies that
enable secure computation on biomedical data, including the discovery of
interpretable patterns, structures, correlations, and cohorts.
- Development of models for the assessment of data security risk and their application
to various scenarios for data exchange, with a special focus on the secure exchange
of genome and health data.
- Investigation of novel computing paradigms for highly efficient, trustworthy distributed
computations on large data sets.
- Design, development, and analysis of cryptography-based privacy-preserving
machine learning services for clinical settings where heterogeneous data exist at
various locations.
- Design, development, and analysis of privacy-preserving performance evaluation of
collaborative machine learning models for distributed clinical settings.
- Investigation of attacks on explainable machine learning models and possible
defense mechanisms to prevent these attacks applicable for medical data.
 

Profile
The ideal candidate will have:
- a Ph.D. or equivalent in Medical Informatics, Machine Learning, Bioinformatics,
Computer Science or a related discipline
- proven experience in applied cryptography, privacy enhancing technologies (incl.
anonymisation, secure multi-party computation, computing on encrypted data),
security protocols, machine learning, medical informatics and, bioinformatics.
- knowledge of medical data and healthcare domain.
- proven records of publications
- proficiency in English

We are committed to enhancing diversity in science, and particularly looking forward to
receiving applications from female scientists and people from underrepresented groups
across cultures, genders, ethnicities, and lifestyles. In case of equal qualification and
experience, physically challenged applicants are given preference. The employment will be
carried out by the central administration of the University of Tübingen.

How to apply
Please send your application (including your motivation letter, curriculum vitae, certificates,
and contact details of two academic references) with the subject [Application Group Lead
MDPPML] via e-mail to Prof. Dr. Nico Pfeifer: mm-sekretariat@inf.uni-tuebingen.de.
Application deadline: 6th of September 2021

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