Student Assistant — CACoM Course Coordination Clinical Applications of Computational Medicine

03.09.2026, Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten

for Winter term, application deadline 15.9.26

Student Assistant — CACoM Course Coordination
Clinical Applications of Computational Medicine (CACoM)
Chair of Data Processing (LDV) · TUM School of Computation, Information and Technology ·
Technical University of Munich
Commitment Period 84 hours in total, spread across the course — on average 4 hours per week
Winter semester 2026/27 — from the first lecture on 22 October 2026 to the end
of March 2027
Language English
Position Apply by Student assistant (f/m/d), paid according to the TUM rates for student assistants
15 September 2026, to martin.daumer@tum.de
The course
CACoM is a project-based course at TUM. Students work in teams of one to seven on data-driven
research projects at the intersection of computation and clinical medicine, alongside lectures from
internal instructors and guest talks from clinicians, researchers and industry partners. Each team is
mentored; some projects are supervised by external collaborators. The semester ends with a
symposium at which every team presents a poster and a one-minute video, followed by
submission of a reproducibility package. The course is led by Prof. Dr. Martin Daumer and runs in
English. See https://cacom.dev.
The role
You are the coordination point of the course for one semester.
• The lectures. You attend the weekly course sessions. Most are remote; some are hybrid, and
for those you are there in person.
• Student groups. You support group formation, keep topic discussion moving to the approval
deadline, and follow each team’s progress through the semester.
• Lecturers and supervisors. You support Prof. Daumer and the other instructors, including
guest lecturers supervising individual projects, in everything organisational around their teams.
• The symposium. You prepare the final symposium with the course team.
• Submissions and grading. You run the submission process for the posters, the videos and the
reproducibility packages, and you assemble the documents the grading is carried out from.
• Correspondence. You handle the course’s day-to-day communication with students,
instructors and external collaborators. From this semester the course runs a ticketing system
alongside email, and you work in it.
Most of this work is written communication on a fixed schedule. The course already has the
structure for it: a published timeline, a correspondence and CC discipline, and the ticketing
system. You run that structure.
The hours are not evenly spread. The topic-approval deadline, the symposium and the submission
deadlines are the peaks; the weeks between them, and the Christmas break, are quieter.
What we ask for
• Enrolment as a student at TUM, at Bachelor’s or Master’s level. A programme in computation,
information and technology, medicine or a related field is an advantage.
• Fluent written and spoken English, at C1 level or equivalent. The cohort is international and all
course business is conducted in English.
• Reliable, prompt, well-organised written communication. You will be answering students,
instructors and external partners, often under a deadline.
• The ability to keep track of many parallel threads — some twenty to forty students in several
teams, each at a different stage.
• Interest in computational medicine. You do not need research experience in it.
Knowledge of German is not required.
What the role offers
• Close involvement in an interdisciplinary course and its clinical, academic and industry
collaborations.
• Direct work with the course leadership and the guest lecturers.
• Experience in coordinating a research course end to end, from topic selection to grading.
Applying
• Deadline 15 September 2026.
• Send to martin.daumer@tum.de, for applications and for questions about the role.
• Subject line [CACoM] Student Assistant Application
• Enclose a short motivation, your CV and a current transcript of records.
Applications are reviewed as they arrive. The selected candidate is sent TUM’s hiring forms and
returns them promptly, so that the appointment is in place for the first lecture.
We strive to raise the proportion of women in our workforce and explicitly encourage applications
from qualified women.
Applications from disabled persons with essentially the same qualifications will be given
preference.
As part of your application for a position at the Technical University of Munich (TUM), you submit
personal data. Please view our privacy policy on collecting and processing personal data in the
course of the application process pursuant to Art. 13 of the General Data Protection Regulation of
the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By
submitting your application you confirm that you have acknowledged the above data protection
information of TUM.

Kontakt: martin.daumer@tum.de