Job Opportunities

The Machine Learning Group consistently seeks exceptional individuals for the following positions:

  • Postdoctoral Researcher
  • Ph.D. Researcher
  • Student Assistant

How to apply

We welcome applications for the positions described below and unsolicited inquiries. In the latter case, candidates can email their applications to sekr(∂)ml.tu-berlin.de, ensuring to include a cover letter, CV/resume, and academic transcripts.

What we are offering

The Machine Learning Group is located in the center of Berlin, close to the public park Tiergarten that spans 2.1 square kilometers. Berlin is one of Germany’s centers for machine learning research and industry, housing three universities and more than 70 research institutes such as the Fraunhofer and Max Planck societies.

Prof. Klaus-Robert Müller, one of Germany’s most-cited scientists, leads the Machine Learning Group while also serving as director of BIFOLD. The Machine Learning Group operates under the umbrella of BIFOLD, which benefits from 22 million EUR in permanent annual funding from the federal state. We are offering:

  • Paid annual leave: 30 days plus December 24th/31st and ten public holidays (Ph.D. and postdoc)
  • Flexible working hours and the possibility to (partially) work from home
  • Family-friendly environment, e.g., childcare services and the possibility of a leave to care for relatives (Ph.D. and postdoc)
  • A cheap public transport ticket (a subsidized version of the Deutschlandticket) for all public transport in Germany, including regional trains (Ph.D. and postdoc)
  • Salary according to Germany’s collective agreement TV-L for federal-level public service employees (Ph.D. and postdoc)
  • A friendly and welcoming culture
  • A group of more than 50 motivated researchers with diverse interests and backgrounds
  • A wide network of academic and industry collaborators
  • Many small offices with modern equipment
  • A large-scale compute cluster with many state-of-the-art GPUs, such as A100
  • An annual multi-day retreat and optional team events like canoeing

Our diverse team brings together expertise from disciplines such as physics, chemistry, and computer science. Applicants are encouraged to explore our research profile and team members to identify areas of common interest. They may also browse our secondary team overview which allows filtering team members by research interests more granularly.

What we are looking for

We seek applications from individuals with a proven track record of excellence in their respective fields. Proficiency in German is not a mandatory requirement unless explicitly mentioned. Our group firmly believes in inclusion, and we invite applications from candidates of all genders, ages, and ethnic backgrounds. We prioritize applications from qualified individuals with disabilities.

Our Team Roles

Postdoctoral Researcher

Applicants should be prepared to provide letters of recommendation upon request. Eligibility criteria include:

  • Ph.D. in a related field such as computer science or physics
  • Demonstrated track record of first-author publications in peer-reviewed venues (e.g., NeurIPS, ICML, ICLR, CVPR, JMLR, TMLR, PAMI, IEEE journals, or domain-specific conferences/journals) or equivalent projects
  • Proven programming experience, e.g., in languages such as Python, C++, Rust, or Julia, frameworks such as PyTorch, TensorFlow, NumPy, or JAX, and version control systems like Git
  • Excellent communication skills and ability to collaborate
  • Proficiency in English
  • Contributions to open-source software are desirable but not required
  • Interdisciplinary and cooperative project experience is desired but not required

Ph.D. Researcher

We fill some of our Ph.D. positions via the BIFOLD graduate school, which admits new candidates every year. Applicants should be prepared to provide letters of recommendation upon request. Eligibility criteria include:

  • Master’s degree in a related field such as computer science or physics
  • Proven programming experience, e.g., in languages such as Python, C++, Rust, or Julia, frameworks such as PyTorch, TensorFlow, NumPy, or JAX, and version control systems like Git
  • Excellent communication skills and ability to collaborate
  • Proficiency in English
  • Publications in peer-reviewed venues are desirable but not required
  • Contributions to open-source software are desirable but not required

Student Assistant

We are seeking motivated and proficient students to join our team, contributing in domains such as teaching and research. Note that it may be possible to split working time between such domains, e.g., allowing students to contribute both to teaching and research. Our needs may vary each semester, so we encourage students with diverse interests and skills to apply. Please submit your application in English to sekr(∂)ml.tu-berlin.de, including the following documents in the PDF format:

  1. Cover letter: Detail your preferred work area or strengths, such as research in general or specific academic domains, teaching, organizational work, web development, or other relevant areas within a research group at a university.
  2. CV/resume: Limit to one page, focusing on qualifications relevant to the role.
  3. Additional documents: Consolidate supplementary materials (e.g., academic transcripts) into a single PDF.

Mandatory eligibility criteria:

  • Enrollment in a bachelor’s or master’s program at TU Berlin or another university
  • Excellent communication skills and ability to collaborate
  • Proficiency in English

Role-dependent eligibility criteria (desired but not always required):

  • Machine learning skills, e.g., as acquired by the courses offered by our group or some equivalent
  • Proven programming experience, e.g., in languages such as Python, C++, Rust, or Julia, frameworks such as PyTorch, TensorFlow, NumPy, or JAX, and version control systems like Git
  • Teaching experience

We also offer positions only for tutoring in our bachelor’s courses. Interested candidates must apply through the faculty IV website (unfortunately, only available in German) and not directly to our group. Non-German speakers may contact sekr(∂)ml.tu-berlin.de for help.