Project Manager and Data Scientist (f/m/d) in Agriculture

Nur für registrierte Mitglieder
München
EUR 55.000 - 70.000
Jobbeschreibung

Project Manager and Data Scientist (f/m/d) in Agriculture

We are seeking a Project Manager and Data Scientist (f/m/d) to start at our Weihenstephan/Freising location, starting February 2, 2025, for an initial period of two years. The Technical University of Munich (TUM), with its approximately 50,000 students, is one of the world’s top universities (top 1 among European universities in the World University Ranking, top 45 in the Shanghai Ranking, top 13 in the Global University Employability Ranking, and top 1 in the SCImago Institutions Ranking Germany). It is committed to excellence in research and teaching, interdisciplinary education, and the active promotion of young scientists. The World Agricultural Systems Center – Hans Eisenmann Forum for Agricultural Sciences (HEF) is one of seven Corporate Research Centers at TUM. The HEF (comprising the HEF office and 32 member chairs) networks all TUM chairs and institutions focused on agricultural sciences, supports collaboration with other agricultural and non‑agricultural science institutions on campus and beyond, initiates research projects, provides professional expertise, and serves as the visible contact for agricultural sciences within and outside TUM. The HEF office team supports these activities in the organization, coordination, and implementation.
13.10.2025, Wissenschaftliches Personal We are seeking a Project Manager and Data Scientist (f/m/d) to start at our Weihenstephan/Freising location, starting February 2, 2025, for an initial period of two years. The Technical University of Munich (TUM), with its approximately 50,000 students, is one of the world’s top universities (top 1 among European universities in the World University Ranking, top 45 in the Shanghai Ranking, top 13 in the Global University Employability Ranking, and top 1 in the SCImago Institutions Ranking Germany). It is committed to excellence in research and teaching, interdisciplinary education, and the active promotion of young scientists. The World Agricultural Systems Center – Hans Eisenmann Forum for Agricultural Sciences (HEF) is one of seven Corporate Research Centers at TUM. The HEF (comprising the HEF office and 32 member chairs) networks all TUM chairs and institutions focused on agricultural sciences, supports collaboration with other agricultural and non‑agricultural science institutions on campus and beyond, initiates research projects, provides professional expertise, and serves as the visible contact for agricultural sciences within and outside TUM. The HEF office team supports these activities in the organization, coordination, and implementation.

Responsibilities

  • You will coordinate and manage collaboration with agricultural use case research projects and, in close cooperation with the DSSC, act as a bridge between agrosystem scientists and experts in different RDM domains (data science, software development, data governance, legal aspects).
  • You will monitor the progress of FAIRagro use cases and support them in developing solutions aligned with the needs of their focal user community.
  • You will support the publication of domain‑specific research data in line with the FAIR principles.
  • You will identify and leverage synergies among use cases, and between use cases and service development teams, initiating and coordinating working groups to foster collaborative development of RDM solutions.
  • You will coordinate and further develop a data integration framework for high‑throughput crop modeling applications.

Qualifications

  • A university degree, preferably a doctorate, in a scientific field relevant to the TUM‑HEF research (e.g., agronomy, crop modelling, data science, geoinformatics).
  • Proficiency in at least one programming language commonly used in the processing of research data (e.g., R, Python), and a solid understanding of ETL processes (Extract, Transform, Load) as applied to scientific data.
  • Good understanding of agrosystem data, including their scales (e.g., crops, cultivation trials, fields, and landscapes), and various data formats (e.g., farm and management data, time series, long‑term field experiments, geospatial data such as remote sensing).
  • Knowledge of research data management, metadata and data publication standards relevant to agricultural sciences is appreciated.
  • A high degree of initiative, along with excellent communication and teamwork skills in an interdisciplinary environment.
  • Very good language skills in German and English, both written and spoken.

Benefits

  • An interdisciplinary working environment that promotes independent action and self‑reliance.
  • Attractive remuneration according to the German Federal State Collective Agreement (TV‑L).
  • Supplementary public service pension scheme (VB‑L).
  • A collegial and open‑minded working environment in a dynamic research institution.
  • Support for specialist and interdisciplinary continuing education and training as well as qualification.
  • Nature‑based, meaningful work just outside Munich.

Application

Women are expressly encouraged to apply. Applications from people with severe disabilities will be given preference if equally qualified. Please submit your application, including the usual documents, in particular your CV, proof of qualifications, and certificates, by email. Please create a PDF document (max. 5 MB; compressed PDF documents, archive files such as zip, rar, etc. cannot be processed and therefore considered!) by November 5, 2025, to benjamin.leroy@tum.de or desiree.bienert@tum.de.
For further inquiries, please contact Dr. Benjamin Leroy (benjamin.leroy@tum.de). Application documents or extensive publications sent by post will not be returned. If you apply, we will collect and process your personal data in accordance with Articles 5 and 6 of the EU GDPR solely for the purpose of processing your application and for purposes related to potential future employment at TUM. After six months your data will be deleted.
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Kontakt: desiree.bienert@tum.de

Contact

Ben Franklin Leroy – Dr. Benjamin Leroy
benjamin.leroy@tum.de

Data Privacy

We treat your personal data with strict confidentiality in accordance with GDPR. For any questions about data handling, please contact the TUM data protection office.