The Berlin Institute for the Foundations of Learning and Data (BIFOLD) at Technische Universität Berlin is offering two fully funded PhD positions in the fields of computer science and data science. These positions are available in the DIMA research group, led by Professor Volker Markl, and the DAMS research group, led by Professor Matthias Böhm. The DIMA group focuses on research in database systems, big data analytics, and the development of information management theory and algorithms, particularly for parallel and distributed processing systems handling large data volumes on heterogeneous processors. Teaching duties include courses such as Informationssysteme und Datenanalyse, Database Technology, and Scalable Data Science: Systems and Methods. The DAMS Lab is seeking a research associate with a focus on system infrastructure for data-centric machine learning pipelines and their efficient, scalable execution in both local and distributed environments. Research topics include language abstractions for ML pipelines, efficient training and inference of large language models (LLMs), compilation techniques for linear algebra programs, runtime kernels, parallelization strategies, ML system internals (memory management, I/O), and support for heterogeneous hardware accelerators. Teaching responsibilities are also part of the role. Applicants must hold a master's degree, diploma, or equivalent in computer science or a related field. Candidates from other domains are welcome if they are willing to address any gaps in computer science knowledge. Essential qualifications include a strong background in data management, applied machine learning, distributed systems, and software engineering, with mandatory programming experience in Python and Java (C/C++ is a plus). The ability to teach in German and/or English is required, with a willingness to acquire missing language skills. Additional desirable skills include teamwork, independent work style, motivation, research methods, scientific writing, and teaching experience. Both positions are fully funded (E13 TV-L salary grade) for up to five years, with options for full-time or part-time employment. The application deadlines are November 15, 2025 (DIMA) and November 21, 2025 (DAMS). Applications should be submitted via email with all required documents in a single file. The university encourages applications from women, individuals with disabilities, and people of all nationalities and backgrounds. For more information, refer to the official job postings and the BIFOLD website.

<p>The Berlin Institute for the Foundations of Learning and Data (BIFOLD) at Technische Universität Berlin is offering two fully funded PhD positions in the areas of computer science, data science, and machine learning. These positions are available in the DIMA research group, led by Professor Volker Markl, and the DAMS Lab, led by Professor Matthias Böhm. Both groups are part of Faculty IV - Electrical Engineering and Computer Science.</p> <p>The DIMA group focuses on research in database systems, big data analytics, and the development of information management theory and algorithms, particularly for parallel and distributed processing systems. Responsibilities include conducting research, developing scalable data science systems, and teaching courses such as Informationssysteme und Datenanalyse, Database Technology, and Scalable Data Science: Systems and Methods.</p> <p>The DAMS Lab specializes in system infrastructure for data-centric machine learning pipelines, efficient training and inference of large language models, compilation techniques for linear algebra programs, and support for heterogeneous hardware accelerators. The group also emphasizes teaching and system-oriented research in data management for the end-to-end data science lifecycle.</p> <p>Applicants should hold a Master’s degree (or equivalent) in computer science, business informatics, or a related field. Required skills include strong programming abilities in Java, C/C++, and Python, as well as in-depth knowledge of SQL databases, declarative query processing, distributed and parallel databases, and data analysis algorithms. The ability to teach in German and/or English is required, with a willingness to acquire missing language skills. Additional desirable qualifications include project management experience, teamwork, industrial internships, research methods, and didactic competence.</p> <p>Both positions are fully funded at salary grade E13 TV-L Berliner Hochschulen, with a duration of up to five years. The funding covers salary and social benefits according to German public sector regulations. The start date is as soon as possible, and both full-time and part-time employment are possible.</p> <p>To apply, candidates should send their application with the reference number and all required documents (cover letter, CV, transcripts, degrees) in a single file (max. 10 MB) by email to [email protected] (for DIMA) or [email protected] (for DAMS). Applications from women, individuals with disabilities, and people of all nationalities and backgrounds are encouraged. The application deadlines are November 15, 2025 (DIMA) and November 21, 2025 (DAMS).</p> <p>For more information, visit the official job postings:<br> <a href="https://www.jobs.tu-berlin.de/en/job-postings/198353">DIMA position</a><br> <a href="https://www.jobs.tu-berlin.de/en/job-postings/198985">DAMS position</a></p>

Technische Universität Berlin, through the Berlin Institute for the Foundations of Learning and Data (BIFOLD), is offering 10 PhD positions as research assistants in the fields of Data Management and Machine Learning. These positions are part of the BIFOLD Graduate School, a leading center for artificial intelligence research in Germany. The research focus includes Data Management, Machine Learning, and their intersection, covering topics such as big data systems, distributed analysis, database systems, data integration, data science pipelines, and advanced machine learning algorithms. Research groups are led by renowned professors including Volker Markl, Klaus-Robert Müller, and others, with opportunities to work on cutting-edge projects in AI, quantum chemistry, and earth observation. Applicants should hold a Master's degree (or equivalent) in computer science or a closely related field, with strong academic records and relevant experience in programming and research. Specific requirements depend on the chosen research area: Data Management applicants should have hands-on experience with big data or database systems, while Machine Learning applicants need strong theoretical and practical ML skills. Interdisciplinary candidates should demonstrate experience in applied ML and data science pipelines. Excellent English communication skills are required, and basic German or willingness to learn is expected. Early research and teaching experience are advantageous. The positions are fully funded, salaried according to TV-L 13 Berliner Hochschulen, and include comprehensive mentoring, funding for conference participation, and access to international academic events. The working environment is international, collegial, and family-friendly. Applications from women, individuals with disabilities, and candidates of all nationalities are encouraged to ensure diversity and equal opportunity. To apply, candidates must submit a single PDF including the application form, motivation letter, CV, academic transcripts, certificates, and publication list by email to [email protected], quoting the reference number IV-531/25. The application deadline is February 13, 2026. For more information, applicants should review the research groups and thesis opportunities on the BIFOLD website.