We are looking for a postdoc to conduct independent research at the intersection of data engineering and machine learning. The research direction should be compatible with the themes of our lab, such as (1) data-centric debugging and testing of machine learning pipelines, (2) data processing in compliance with legal regulations, or the (3) automation of data validation and preparation for ML. Software and data artifacts resulting from the research should be made available under open source licenses or contributed to existing open source projects.

Further tasks of the position include the collaboration with PhD students, the coordination with other research groups in BIFOLD and external partners, the supervision of master/bachelor theses and teaching activities.

• Successfully completed university degree (Master, Diplom or equivalent) and PhD in computer science or artificial intelligence
• Strong research background in data management for ML (e.g., data debugging, data preparation, data provenance, data integration, data debiasing, data-centric AI, ML pipelines, responsible data management, ML Systems)
• Publication record in international refereed academic conferences such as SIGMOD, VLDB, SIGIR, ICLR, KDD, NeurIPS or ICML
• The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills

Desirable:

• Experience in supervising Master/PhD students
• Teaching experience

Please send your written application, quoting the reference number, together with the usual application documents (i.e. at least a cover letter, CV, degree certificates, transcripts of records, etc.) to Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Management von Data Science Prozessen, Prof. Dr.-Ing. Schelter, TEL 9-2, Ernst-Reuter -Platz 7, 10587 Berlin, by e-mail (one PDF file, max. 5 MB) to: schelter@tu-berlin.de.

For reasons of cost, application documents sent by post will not be returned. Please submit copies only.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 214041.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.