Volker Markl
9 months ago
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PhD Positions in Data Management and Machine Learning at Technische Universität Berlin (BIFOLD) Technische Universität Berlin in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Positions are salaried according to salary grade 13 TV-L Berliner Hochschulen. Funding includes comprehensive mentoring, support for conference visits, and guest scientist programs. No explicit stipend amount is mentioned, but positions are fully funded as research assistants without teaching obligations.
Deadline
Expired
Country
Germany
University
Technische Universität Berlin
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Keywords
About this position
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.
Funding details
Positions are salaried according to salary grade 13 TV-L Berliner Hochschulen. Funding includes comprehensive mentoring, support for conference visits, and guest scientist programs. No explicit stipend amount is mentioned, but positions are fully funded as research assistants without teaching obligations.
What's required
Applicants must have a completed academic university degree (Master, Diploma, or equivalent) in computer science or closely related fields with a focus on at least one BIFOLD core area and very good grades. Good programming skills (e.g., Python, Java, Scala, C/C++, Rust) are required. For Data Management: hands-on experience with big data or database systems. For Machine Learning: strong knowledge of ML theories and methods, practical experience with ML algorithms, and frameworks like NumPy, PyTorch, TensorFlow, or JAX. For intersectional topics: experience in applied ML, data integration, data science pipelines, and optionally multi-modal data representations. Excellent English communication skills are required; basic German or willingness to learn is expected. Early research and paper writing experience, as well as teaching competence, are advantageous. Highly motivated, curious, and results-oriented candidates with strong academic records are sought.
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Professors
Professor
Germany
Research Interests
Artificial Intelligence
Database Management
Computer Science
Information Technology
Data Science
Professor
Germany
Research Interests
Artificial Intelligence
Database Management
Machine Learning
Quantum Chemistry
Distributed System
Professor
Germany
Research Interests
Artificial Intelligence
Database Management
Machine Learning
Data Science
Computer Science
Professor
Germany
Research Interests
Database Management
Artificial Intelligence
Quantum Chemistry
Computer Science
Big Data
Professor
Germany
Research Interests
Artificial Intelligence
Database Management
Computer Science
Data Science
Information Technology
Professor
Germany
Research Interests
Cartography
Artificial Intelligence
Hyperspectral Imaging
Remote Sensing
Computer Vision
Professor
Germany
Research Interests
Artificial Intelligence
Database Management
Machine Learning
Malware Analysis
Data Science
ApplyKite TwinLearns as you applyMake your next move.
Prepare your application
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