Linde/MDSI PhD Fellowships

This unique fellowship program is designed to foster interdisciplinary collaboration and promote innovative approaches to addressing data science challenges.

Download Call for Linde / MDSI PhD Fellowships

Download Letter of intent for Linde / MDSI PhD Fellowships

All Linde/MDSI PhD Fellows across different disciplines will become an essential part of MDSI's thriving and dynamic research atmosphere. They will participate in the specially tailored MDSI qualification program. Furthermore, they will be co-located at the facilities of the institute as needed. Collaboration and interaction with fellows and faculty from other areas of research is highly supported.

Applications are welcome in:

All areas of data science and machine learning, their mathematical foundations, and their application in the various scientific fields represented at TUM.

Your motivation letter should outline your interest for the PhD thesis and connection to the above research areas (i.e. contain a research plan). Please also elaborate on the research groups with which you see a fit and in particular on the group that you would like to host you for the PhD at TUM. In addition, please name your potential thesis supervisor. Eligible as supervisor are all professors at TUM (https://www.professoren.tum.de/en/; also see Regulations on the Awarding of Doctoral Degrees at TUM) including TUM Junior Fellows (https://www.professoren.tum.de/en/tum-junior-fellows) with a thematic fit to the general areas described above.

Eligibility:

  • Excellent master's degree (or equivalent)* in computer science, mathematics, engineering, natural sciences or other data science related social disciplines.
  • General admission requirements for a doctorate at TUM are met as defined here: https://www.gs.tum.de/en/applicants/application/.
  • Membership in the TUM Graduate School (as per supervision agreement) cannot have started before 09 January, 2022.

Please provide the following documents:

  • CV including a list of publications and awards (if applicable).
  • Scanned transcripts of certificates (bachelor's degree, master's degree including transcript of records, other degrees or awards).
  • Motivation letter as described above (max. 3000 characters).
  • Names and addresses of two references who can provide letters of recommendation. Please inform the reference persons listed to send the letters of recommendation directly to the MDSI before the call closes (to application@mdsi.tum.de, e-mail subject: Letter of recommendation - <your name>).
  • Support letter of the chair who is willing to act as a host (see attached). In this letter, the host agrees to supply one half of the PhD funds.

Please submit your application as one pdf file to the following e-mail address: application@mdsi.tum.de (e-mail subject: Application PhD fellowship - <your name>), application deadline is 09 January, 2022. Notification about the results is planned for March, 2022.

Successful applicants will be hired in line with the current German collective pay agreement, up to TV-L E13. The fellowship period will have a maximum duration of three years. Applications from disabled persons with essentially the same qualifications will be given preference. TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women.

As part of your application for a position at the Technical University of Munich (TUM), you are transmitting personal data. Please note our data protection information in accordance to Art. 13 General Data Protection Regulation (GDPR) for 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 (https://portal.mytum.de/kompass/datenschutz/Bewerbung/#English).

*If you are still studying for your master's degree you may send a bona fide statement from the university, stating the examination marks already obtained. In addition, you will have to finish your master's studies before starting the PhD, i.e. no later than June, 2022.