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Sitemap > Bulletin Board > Student assistants, internships, student research projects

Student assistants, internships, student research projects

Here you will find positions for student assistants and internships at the Technical University of Munich, and student research projects. Job advertisements should be entered by the respective institutions themselves. This requires employee rights in the portal. This is automatically the case for all employees listed in TUMonline. Instructions can be found in the quick guide for job advertisements (in German) and (in more detail) in the Best Practice Manual for Job Advertisements (in German) (pdf).
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01.08.2026
Master Thesis: Quantum Sensor Characterisation

Want hands-on experience with real quantum hardware? Join an innovative quantum technology environment at the Garching Research Campus, working alongside a team pushing the boundaries of quantum sensing. We are looking for a motivated TUM Master student to support us in performing cryogenic measurements to characterize our sensors, and to help further develop our unique automatic cryogenic prober — a one-of-a-kind system in the field.
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Kontakt: career@munich-quantum-instruments.com

31.07.2026
Abschlussarbeit (Bachelor/Master) – Leistungsdiagnostik mit Wearables: Professur für Experimentelle Trainingswissenschaft

Im Rahmen eines durch die EU geförderten Innovations- und Forschungsprojekts ist an der Professur für Experimentelle Trainingswissenschaft eine Abschlussarbeit mit aktiver Mitarbeit bei der Datenerhebung (Laufband-Spiroergometrie, EMG, NIRS, IMUs u.a.) zu vergeben.
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Kontakt: lars.heinrich@tum.de

31.07.2026
Praktikant/in (m/w/d) – Leistungsdiagnostik mit Wearables: Experimentelle Trainingswissenschaft

Die Professur für Experimentelle Trainingswissenschaft sucht ab sofort bzw. flexibel eine/n Praktikant/in zur Unterstützung in der umfassenden Datenerhebung im Bereich der Leistungsdiagnostik mittels Wearable-Technologien.
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Kontakt: lars.heinrich@tum.de

29.07.2026
Development of Chromatographic Strategies for the Purification of Bioactive Lectins from Fungal Mycelium


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Kontakt: Bhagyeshri Ulhas Mantri; b.mantri@tum.de

29.07.2026
Development of an Enrichment Strategy for Lectins from Submerged-Grown Agrocybe aegerita Mycelium

Bachelor’s / Semester /Master’s thesis
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Kontakt: Contact person: Bhagyeshri Ulhas Mantri; b.mantri@tum.de

29.07.2026
Masterthesis/Internship (m/f/d) – Characterization and evaluation of the electronic-nose sensor array

We are looking for a motivated master's student intern to join the electronic-nose (Enose) AI diagnosis Project for a three-month internship, starting as soon as possible, focusing on experimental characterization and evaluation of the electronic-nose sensor array.
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Kontakt: shanye.yang@tum.de

28.07.2026
Working Student/Master Thesis Quantum Sensor Photonics (Deep Tech Startup)

Join Munich Quantum Instruments (MQI), a deep tech startup developing scalable photonic quantum sensors, as a Master's student working hands-on on 3D-printed optics, assembly, and characterization of next-generation quantum sensors for applications like quantum computing and deep space communication.
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Kontakt: career@munich-quantum-instruments.com

27.07.2026
Master Thesis on Electrochemically Controlled Selective Diazotization and Azocoupling Chemistry (Flexible Starting Dates)

We are seeking a Master's thesis student on the electrochemical synthesis of diazonium compounds, background in lab work and interest in organic synthesis and electrochemistry are required.
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Kontakt: pooja.sindhu@tum.de

24.07.2026
Real-Time Optimization Strategies for Predictive Motion Control in Space Robotics

Master’s Thesis / Internship Opportunity

Master’s Thesis / Internship

Real-Time Optimization Strategies for Predictive Motion Control in Space Robotics (f/m/x)

Space robotics is an emerging field of growing relevance for applications such as on-orbit servicing, on-orbit assembly, and active debris removal. In these domains, robotic motion and interaction take place in highly constrained environments and under strict computational and safety requirements. Recent research has shown that Model Predictive Control (MPC) can provide perfromant motion control while explicitly accounting for constraints and uncertainties.

Robotic control problems are inherently nonlinear. Therefore, applying Nonlinear Model Predictive Control (NMPC) in real time requires an efficient formulation of the optimal control problem, together with a carefully selected discretization and solution strategy. Previous work has investigated an offline optimization procedure for identifying the most effective discretization methods. This thesis will investigate convexification methods to improve runtime performance on space-representative hardware while maintaining satisfactory closed-loop performance.

Your Contribution

We are seeking a motivated master’s student with an interest in space robotics to implement an onboard model predictive controller.

Your Tasks

  • Implement an existing NMPC controller on space-representative real-time hardware.
  • Investigate successive convexification strategies for nonlinear operational constraints.
  • Derive bounds on the model mismatch introduced by convexification.
  • Benchmark runtime performance and closed-loop behavior on real-time hardware.

Your Qualifications

  • Currently enrolled in a master’s program in aerospace engineering, mechatronics, computer science, robotics, mathematics, or a related field.
  • Strong programming skills in C/C++; experience with real-time or embedded implementation is a plus.
  • Working knowledge of MATLAB or Python is preferred.
  • Strong interest in space robotics or spacecraft dynamics.
  • Familiarity with Model Predictive Control and numerical optimization is an advantage.

We Offer

  • The opportunity to work on a real-world research problem relevant to autonomous space missions.
  • Collaboration within a leading research institute in space robotics.
  • Insight into robust model predictive control for safety-critical systems.

This thesis is ideal for students interested in embedded optimization, numerical simulation, and space applications who enjoy translating advanced algorithms into efficient, high-performance implementations.

Supervisors: Peter Kötting and Roberto Lampariello


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Kontakt: Peter.Koetting@dlr.de, Roberto.Lampariello@dlr.de

24.07.2026
Real-Time Optimization Strategies for Predictive Motion Control in Space Robotics

This thesis is ideal for students interested in embedded optimization,numerical simulation, and space applications who enjoy translating advanced algorithms into efficient, high-performance implementations.
read more

Kontakt: Peter.Koetting@dlr.de, Roberto.Lampariello@dlr.de

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