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Technical University of Munich

Job Posting: Student Assistant (f/m/d)

To support the teaching team of the project week “Data Ethics in Practice: Dashboarding Indigenous Data Sovereignty with Local Contexts”, TUM School of Social Sciences and Technology, Technical University of Munich (TUM)

Focus: Teaching Assistance / Project Week Management

Duration: 1 October 2026 – 30 April 2027, 7 hours per week

About us

We are the teaching team located at the Chair for Chair for Philosophy and History of Science and Technology, TUM School of Social Sciences and Technology, and in the Ethical Data Initiative at the TUM Think Tank.[1]

We are responsible for the project week “Data Ethics in Practice: Dashboarding Indigenous Data Sovereignty with Local Contexts,” which will take place in January 2027. The project week offers a dynamic, interdisciplinary “data clinic” format, where TUM Master’s and Bachelor’s students collaborate with external partners on real-world challenges in data governance and ethics. Guided by the teaching team, participants engage in interactive sessions to explore responsible data practices, ethical decision-making, and policies related to issues such as privacy, transparency, discrimination, or accountability. The data clinic bridges theory and practice, empowering students and partners with the tools to navigate complex ethical questions and promote responsible data cultures.

For the project week January 2027, we will collaborate with LOCAL CONTEXTS (localcontext.org), an Indigenous-led not for profit organization that works internationally to support Indigenous data sovereignty through an innovative system of data labelling. Local Contexts is a partner of the Ethical Data Initiative at the TUM Think Tank and will, together with the teaching time, provide the “data ethics challenge” for the project week.

Your responsibilities include

  • Support logistical and communication tasks for the project week
  • Coordinate with partner organizations and assist with communications
  • Help prepare materials and manage technical requirements for the project week
  • Assist in organizing and supporting teaching sessions during the semester and assist in writing and editing reports
  • Contribute to course management, including setting up and maintaining the Moodle page
  • Support students throughout the semester and help gather and compile feedback
  • Support creating a poster about data clinic and assist with organizing the final project fair

Your profile

  • You are enrolled as a Master student (e.g. in STS, RESET, Sociology, Communication Studies, Political Science, Management, Business Administration, Marketing, Media, Design, or related fields)
  • Reliable, independent, and proactive working style
  • Strong organizational and project management skills
  • Strong communication skills and ability to work in a team
  • Proficient in Microsoft Office programs
  • Excellent command of English (knowledge of German is not required but an advantage)

What we offer

  • Flexible working hours during the semester
  • Being part of an engaged, interdisciplinary teaching team at the Chair for Philosophy and History of Science and Technology and the Ethical Data Initiative at the TUM Think Tank
  • Experience supporting an innovative “data clinic” format that bridges theory and practice
  • Get insight into current debates and practices in data ethics, governance, and responsible data use
  • Opportunities to develop organizational, communication, and project management skills
  • The opportunity to contribute to an exciting, student-centered project week taking place in January 2027

Conditions

  • Working hours: approx. 7 hours per week
  • Start date: 1 October 2026, for 7 months
  • Compensation: according to standard hourly rates for student assistants

Application

We are committed to increasing diversity in research and teaching and particularly encourage applications from women and non-binary individuals. Applicants with disabilities will be given preferential consideration in cases of equal qualification.

Please send us a short motivation letter, your CV, and a recent study transcript by July 31, 2026,

via email to: Kim Hajek (kim.hajek@tum.de) & Paul Trauttmansdorff (paul.trauttmansdorff@tum.de) 

If you have any questions, feel free to contact us at the email address above.

 

[1] We are Prof. Dr. Sabina Leonelli, Dr. Kim M. Hajek, Dr. Paul Trauttmansdorff

Job Posting: PhD Scholarship in Philosophy and/or Social Studies of Modelling (36 months, fixed term)

We are looking for a PhD student with a strong background in the philosophy and/or social studies of science and technology. The position is part of the Horizon MSCA Doctoral Network “Towards sustainable computational fluid dynamics” coordinated by the Institut National Polytechnique de Toulouse (INPT). The PhD student will be part of a group of largely modelling PhD students all trying to make computational fluid dynamics modelling more sustainable in a comprehensive sense. This will involve a collaborative approach to working with modellers analysing modelling practices within their multiple institutional, social, and epistemic contexts and identifying opportunities for and barriers against more sustainable approaches. The successful candidate will have strong empirical and analytical skills in the study of science and technology while also having an interest in and ability to engage fluid dynamics modelling as a heterogeneous set of practices. 

About us 

This opportunity is offered by the Chair for Anthropology of Science & Technology (Professor Niewoehner) at the TUM School of Social Sciences and Technology (SOT), in collaboration with the Chair for the Philosophy and History of Science and Technology (Professor Leonelli). The PhD student will be carrying out research as part of the FairCFD Horizon project, starting preferably in January 2026 with funding for 3 years (65% of E13 salary scale). The chairs comprise interdisciplinary, public-interest-minded, international and impact-oriented teams based at the TUM SOT. We have world-leading expertise in the social studies, philosophy, and history of science, particularly modelling, dataintensive research and the governance of data and AI. Both chairs are located within the Department of Science, Technology and Society, which is dedicated to understanding the larger social, political, ethical and legal dimensions of science and technology. Embedded in TUM’s unique innovation ecosystem, we are committed to enabling a more responsible and sustainable engagement with science and innovation through social science research, teaching and public dialogue – often in collaboration with partners from technical fields. The TUM STS community strives to provide new intellectual and practical resources for dealing with the challenges of highly technologised societies, and to train future leaders with a unique sensibility for the critical interface between science, technology and society. As one of Europe’s largest hubs for STS, we are a lively intellectual community of 70+ researchers from numerous disciplines and fields of specialization. As a department, we deliver 2 Master’s programs and design STS content for the School’s PhD program. We offer regular public lectures and symposia, weekly discussion groups, and visiting researcher programs. We maintain close collaborative ties to other parts of TUM as well as to leading HPS and STS centres in Germany and around the world.

We invite the researcher taking on this position to become a core contributor to the Horizon project “Towards Sustainable Computational Fluid Dynamics” (FairCFD), a training programme focused on the development of novel modelling tools where the PhD candidate will have the opportunity to study and contribute to these technical developments from the viewpoint of the social and philosophical studies of science. 

About the FairCFD project

Over the past seven decades, Computational Fluid Dynamics (CFD) has enabled increasingly efficient industrial processes achieving both economic and environmental gains through the reduction of testing, prototype development and creation of more efficient end-products. For instance, the usage of CFD in Boeing allowed a reduction of wind-tunnel experiments by 87% between the late 1970’s and the late 1990’s, corresponding to a reduction of energy consumption which can be estimated as 8.7 107 kWh 1 while reducing the fuel and consumables requirements for these services.

Up to the end of the 20th century, “traditional CFD” was driven by a paradigm of three pillars, as sketched in the left side of figure 1. The first is fidelity, defined as the ability to accurately reproduce all details of the flow. The second is the requirement for acceptable performance, defined by end-users as the ability to obtain reliable results in reasonable wall-clock time on available hardware. Thirdly, the quest of generality, namely the ability to simulate a variety of flows within a single software package has been a target in the development of commercial solvers which are the main tools used by industry. In the past 2 decades, the development and use of CFD underwent four major pivots. Firstly, the appearance of a new generation of open-source software has accelerated the usage of CFD in many areas of engineering, especially among SMEs. Secondly, the development of High-Performance Computing (HPC), largely driven by ever-growing demand for larger CFD simulations, led to a shift from performance towards efficiency, defined more precisely as minimisation of computer resources required for a given simulation. Concomitantly, the objective of fidelity has been progressively replaced by accuracy, defined as the ability to accurately predict global results of practical importance, such as drag, regardless of a precise description of fine flow details. The third major pivot is the appearance of Artificial Intelligence (AI), currently a major revolution in all sectors of Information Technologies. In the field of CFD, usage of AI aims at replacing or complementing traditional physics-based approaches by data-driven ones, using Machine-Learning (ML). Such approaches allow enormous gains of time, in a way that can be related to the astonishing efficiency of an artificial intelligence like ChatGPT compared to a human translator for text translation tasks. However, the cost of this efficiency is the training phases of the AI, which are timeconsuming, and require a large amount of data which must be previously generated, again with a cost. The fourth major pivot, which is only in its infancy, is the recognition that usage of CFD has a cost: energetical, environmental, and social-ethical, meaning the wider societal implications of new simulation practices. Despite its importance in view of current sustainability concerns, only very few studies have considered these aspects. The ambition of the FairCFD network is to work towards the establishment of sustainable CFD as a new paradigm within the community of academic, industrial and educational actors, advancing efficiency, measuring and promoting frugality without compromising accuracy.

Requirements 

The successful applicant will be expected to conduct research leading to the award of a PhD degree, by examining the activities of the FairCFD Network and particularly the ways in which qualitative methods can contribute towards the scientific goals of the project. The applicant will be expected to use ethnographic fieldwork and interviewing techniques to explore the idea of ‘frugality’ as conceptualized and implemented by members of the FairCFD network, thereby producing a study of the social and epistemological foundations of scientific modelling in CFD, with critical reflection of findings in the wider contexts of knowledge production in CFD and sustainability writ large. This doctoral research will be situated in the context of a wider subproject looking into the epistemic practices and cultures of the 14 fluid dynamics PhD projects and their respective institutions and wider intellectual and technological environments with a particular focus on the development and use of sustainability metrics. This will also include the industrial partners in the consortium as the sustainability of new simulation techniques does not only hinge on their conception under lab conditions but also their actual deployment in real-world contexts of industrial practices. Through systematic literature reviews, rapid ethnographic assessment of the institutions and key labs, participant observation within the working practices and training events of the network, and interviewing of key researchers, the subproject will gather an empirically saturated understanding of notions of sustainability that are being inscribed into innovative simulation practices. This comprises ecological dimensions but also wider aspects of social order, equity and moral concerns. Potential deployment and application of the new techniques in industry will be analysed through interviews with key personnel at the industrial partners.

We are excited to collaborate with a highly motivated PhD candidate who shares our deep interest in exploring conceptual, educational, social, and governance issues that emerge in the context of scientific modelling. 

The candidate also brings the following qualifications:

 • Masters-level studies or equivalent qualification/experience in the philosophy, history and/or social studies of science or a related field of study. • Demonstrated interest in scientific models and/or data-intensive methods in the natural (and preferably the physical) sciences. 

• Demonstrated interest in the philosophy of science in practice and STS qualitative methods.

 • Excellent written and verbal communication skills.

 • Able to communicate complex and conceptual ideas to a range of groups.

 • Able to balance the pressures of research, administrative demands and competing deadlines. 

• An understanding of the importance of equality and diversity within an organisation and a commitment to helping create an inclusive culture.

 • Interest and ability to engage in organizational tasks supporting the FairCFD project, such as developing events and training to engage project members and associates

 • Interest and ability to develop funding applications both nationally and internationally in collaboration with the STS Department and the FairCFD team 

• Intellectual curiosity and an open mindset, and the ability and motivation to work both independently and as member of the team

• Organizational skills and excitement to work in a fast-paced, cross-cultural, and interdisciplinary environment 

 • Very good English skills, with knowledge of the German and French language as a plus (but not necessary).

Tasks 

• Conduct research for FairCFD on research inequity and epistemic injustice, resulting in internationally leading publications 

• Participate in weekly project meetings and in conferences and events relating to the project, and present outputs as required 

• Support the project through administrative and organizational tasks as necessary

 • Contribute to the intellectual life and community of the STS Department and the Chairs of Anthropology and of Philosophy and History of Science and Technology

Our offer 

We offer exciting opportunities to participate in cutting-edge research, education, and outreach in a highly collaborative, interdisciplinary, and internationally networked environment, tackling some of the hardest problems in the field of science studies and philosophy/history of science with a commitment to the public good. We as well offer the opportunity to build your own research agenda around relevant topics. We invite you to join us on the inner-city campus of TUM.

What to expect 

• The possibility of successfully acquiring a PhD degree by carrying out research and developing high-level publications in this domain

 • Working in a cutting-edge research, training, policy and outreach effort funded by Horizon Europe, thereby acquiring skills in interdisciplinary research and teaching 

• Working in a highly collaborative team of researchers from science studies, philosophy and history of science, data studies, agricultural/health/data science 

• The opportunity to participate in collaborative academic publishing and engage with the broader scientific community through workshop and/or conference visits. 

• Mentorship and continuous support in building an independent academic and professional profile. 

• Remuneration according to the collective agreement for the public service of the federal states (TV-L) in the classification TV-L 13 to the extent of 65%. 

The chosen candidate will be employed at the TUM Chair of Anthropology of Science and Technology. The employment contract is limited to 36 months.

Application 

We look forward to receiving your informative documents until the 15 January 2026 (cover letter, CV and references, summarized in a single PDF file). We are happy for cover letters to provide details of research plans and aspirations of the candidates. We will review applications on a continuous basis. Hence, they should be submitted as early as possible via e-mail to Victoria Tommasini: victoria.tommasini@tum.de. We expect to invite selected candidates for interviews commencing the week of the 20th of October. Shortlisted candidates will be informed of the outcome by November 15th at the latest. If you have any questions regarding the application process, please reach out to Joerg Niewoehner: joerg.niewoehner@tum.de. TUM is an equal opportunity employer and explicitly encourages applications from women and gender-non-binary persons. The position is suitable for disabled persons. Disabled candidates with essentially the same qualifications and scientific performance as other candidates will be given preference. Find out more about us at www.tum.de. 

Data Protection Information 

When you apply for a position with TUM, you are submitting personal information. With regard to personal information, please take note of the data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

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