More information

Internship Projects 2027

Group (Institute) Project Title(s)
Research Area/Keywords
Duration in weeks Student Background
Jan Brugués TUD PoL

Dissecting energy costs of mitotic spindle

biophysics/self-organization, energy dissipation, quantitative imaging, mathematical modeling

project under the supervision of Shuzo Kato

12 weeks Physics, Life sciences, Engineering
Oliver Bruns TUD Medical Campus

Label-free imaging and spectroscopic characterization of tissue contrast in the shortwave infrared for surgical oncology applications

oncology, functional imaging, shortwave infrared, label-free, Raman, absorption-based

12 weeks biology, life sciences, medicine, computer science, physics, chemistry (but not theoretical/mathematics)
Oliver Bruns TUD Medical Campus

Modification, extension or development of surgical microscopes, endoscopes and back-table systems for surgical oncology applications

surgery microscopy, endoscopy, oncology, functional imaging, shortwave infrared, fluorescence, Raman scattering, absorption-based

12 weeks electrical, mechanical or other engineering; computer science; physics (programming, CAD design, optics or generally technological understanding)
Anna Czarkwiani TUD CRTD

In vivo micro-CT imaging of regenerating otoconia in the axolotl

axolotl, regeneration, gravity sensing, balance disorders

12 weeks (life science, engineering, computer science, physics, mathematics, medicine): life science
Stefan Diez TUD B CUBE, TUD PoL

Investigating the influence of microtubule lattice conformation on bidirectional vesicular transport using an in vitro reconstituted assay

Expanded and Compacted Microtubules, Molecular Motors, Kinesin, Dynein, Liposomes, Intracellular Transport, In Vitro Reconstitution, Fluorescence Microscopy (TIRF)

12 weeks Biophysics, Biochemistry, Life Sciences or Biotechnology
Tian Qiu DKFZ

AI-enabled magnetic tracking of endoscopic instruments

Magnetic localization, surgical image registration, machine learning, endoscopy, minimally-invasive surgery

12 weeks Engineering, Computer Science or Medicine
Shervin Safavi TUD Medical Campus

Staying alive: how internal needs shape behavior and neural circuits in embodied agents

Computational neuroscience and NeuroAI; embodied reinforcement learning, homeostatic regulation, adaptive decision-making, brain-body interaction, naturalistic behavior, interpretability of neural networks

→ Detailed information as PDF

12 weeks Computer science, physics, mathematics, engineering, neuroscience/life sciences (other backgrounds are also welcome). Comfort with programming (Python), ideally prior experience in neuroscience or reinforcement learning.