Postdoc Position in Advanced Analytics

Technische Universität München (TUM)

For the Chair of Advanced Analytics in Manufacturing Management, which is part of the Heilbronn Data Science Center and the TUM School of Management at the TUM Campus Heilbronn, we are looking for a full time position (100%) for an initial period of three years from April 2026 or earlier:

Postdoc Position in Advanced Analytics

About us
The TUM Campus in Heilbronn is part of the renowned Technical University of Munich, one of the top universities in Europe. It is distinguished by excellence in research and teaching, interdisciplinarity, and talent development. Additionally, it maintains strong alliances with companies and scientific institutions worldwide. TUM is one of Germany's first three Excellence Universities. Furthermore, the TUM School of Management is the first management school at a technical university in Germany to receive Triple Crown accreditation. Worldwide, only about 80 institutions (approximately 1%) hold this distinction. The Heilbronn Data Science Center is a research institution of TUM Campus Heilbronn that uses data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains.

About our group
Prof. Dr. Alena Otto holds the Professorship in Advanced Analytics in Manufacturing Management in the Department of Operations & Technology and Heilbronn Data Science Center at the Technical University of Munich, Germany. Prof. Otto is ranked among the top 60 researchers under 40 in Business Administration with the strongest publication record, according to forschungsmonitoring.org (2022). She has received several prestigious scientific and industry awards, including the Dissertation Award of the Operations Research Society (GOR e.V.), the OptWare Award of the “Initiative Wissenschaft und Automobilindustrie,” and the “Commended Paper Award” of the IFAC MIM conference. Prof. Otto actively engages in academic governance, serving as an editorial board member of leading scientific journals as well as a program committee member and session/stream/track organizer of major scientific conferences, such as IFORS 2026, EURO, TRISTAN XI, Odysseus, and the Aussois Workshop on Scheduling. Beyond academia, she has extensive industrial experience and collaborations with Volkswagen, Deutsche Bahn, SSI SCHÄFER, and various “hidden champion” companies in Germany and abroad.
Our group envisions production as a dynamic, interconnected ecosystem spanning multiple locations and entities, where complex constraints and resource interdependencies – among people, machines, and robots – demand the deployment of intelligent algorithms for orchestration, informed decision-making, and planning. Our research pioneers such algorithms grounded in cutting-edge Data Science techniques, with a focus on intelligent exploitation of problem structures, performance, scalability, and robustness. Working at the intersection of disciplines, we rigorously apply and refine these innovations on real-world challenges, ensuring our work addresses the sector’s most urgent needs. Particular attention is given to optimization under uncertainty, the optimization of systems with dynamically incoming information, and the optimization of data collection. Through this research, we contribute to shaping the future of production and logistics.
Our team places particular emphasis on fostering the careers of young scientists. We are very proud of our group members, who have received international scientific awards, participate in joint doctoral programs (co-tutelle) with leading international universities, undertake research stays with globally recognized research groups, and complete internships at companies and technology transfer organizations.

Research focus and tasks of the Postdoc position
You engage in one of our two research fields:

• Multistage planning under uncertainty (e.g., aggregation/disaggregation in dynamic programming, decompositions and stochastic programming, competitive analysis, hybrid combinatorial and AI solution approaches)
• Integrated supply chain planning (topical side: e.g., variants of production routing problem, flexible job shop problem; methodological side: e.g., advanced decomposition algorithms, customized constraint propagation techniques, hybrid combinatorial and AI solution approaches).

Additionally, you will be involved and collect experience in supervision of PhD students, teaching, and further academic and administrative affairs of our professorship.

Your profile

• PhD in Operations Research, Data Science, Applied Mathematics, or a related field
• Proven publication track in highly-ranked relevant scientific journals and conference proceedings
• Completed Master's degree in Mathematics, Statistics, Operations Research, Industrial Engineering, Computer Science, Data Science or a related field
• Strong mathematical and analytical skills for model formulation, optimization, and problem analysis
• Strong programming skills (e.g., in Python, C++, or other programming language)
• Experience in working with off-the-shelf optimization software, such as Gurobi or IBM ILOG CPLEX
• Strong motivation and ability to conduct independent scientific research
• Excellent communication skills in English (both written and spoken)
• Excellent organizational skills
• Proficiency in the German language is an advantage but not required
• High motivation and enthusiasm for working in an interdisciplinary research environment
• Interest and ability to lead PhD students and closely engage in high-profile international collaborations
• Financial support for participation in leading international conferences and workshops

We offer

• Self-determined work related to interdisciplinary research projects
• Opportunities to engage in high-profile international scientific collaborations
• Access to advanced training opportunities and opportunities for academic career development
• Access to case studies, collaborations with industry experts, and demonstrations
• A diverse and inclusive working environment
• The opportunity to work in a vibrant scientific environment
• A modern well-equipped office on the Bildungscampus Heilbronn, incl. amenities such as kitchen and shower
• Possibility to partly work from home
• Technical equipment and necessary software applications and subscriptions
• Access to advanced training opportunities for professional development

Application process
We look forward to receiving your application documents (one-page letter outlining your motivation and research plan, diploma, transcripts of records, CV, two most significant publications or working papers, IELTS/ TOEFL/GRE certificates if available, other certificates) by December 15, 2025, as a single PDF document via e-mail to jobs.udsm@mgt.tum.de (contact person: Ms. Elke Kröber) using the subject “Postdoc Advanced Analytics”.

Or by post to:
TUM School of Management
HDSC
Elke Kröber
Bildungscampus 2
74076 Heilbronn

If you apply by post, please send us copies only, as we will unfortunately not be able to return your application documents once the process has been completed.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women. Payment will be based on the Collective Agreement for the Civil Service of the Länder (TV-L) up to a classification in pay group 13 with appropriate qualifications.

Note on data protection:
As part of your application for a position at the Technical University of Munich (TUM), you submit personal data. Please note our data protection information in accordance with Art. 13 of the General Data Protection Regulation (GDPR) on the collection and processing of personal data in the context of your application. By submitting your application, you confirm that you have taken note of TUM's data protection information.