Postdoctoral researcher for the Heidelberg Institute of Global Health
Heidelberg, DE
vor 5 Tg.

Postdoctoral researcher for the Heidelberg Institute of Global Health (m / f / d)

full- or parttime - JobID : P0025V519

at the earliest possible date searched for, the Heidelberg Institute of Global Health (HIGH).

The position is limited to 3 years, with the possibility of an extension.

The Institute of Global Health at Heidelberg University, Germany’s oldest university and a leading hub for health-related research in Europe, is looking for an outstanding postdoctoral research fellow.

The researcher will work under the mentorship of Dr. Pascal Geldsetzer and receive a designation as visiting researcher at the Stanford University School of Medicine.

Tasks and responsibilities

The postdoctoral fellow will work under the guidance of Dr. Pascal Geldsetzer and other researchers at both Heidelberg University and Stanford University, including both population health researchers and computer scientists.

The researcher will help with expanding the group’s dataset for analysis, as well as building and evaluating convolutional neural networks.

The broad aim of this research is to test whether satellite imagery along with other geo-referenced publicly available data (e.

g., data from OpenStreetMaps, climate and weather variables, and infrastructure-related variables) could be used to monitor important health indicators in low- and middle-income countries at a highly granular geographic and temporal level.

In addition to this core project, the research group works on a wide variety of research, with foci being medication effectiveness, health services research, and population health issues.

The fellow will be expected to publish in high-impact peer-reviewed journals.

The postdoctoral fellow will have the opportunity to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students.

The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so.

The salary is paid according to the German TV-L system (the salary agreement for public service employees). As an equal opportunity employer, the HUK is committed to increase the percentage of female scientists and, therefore, especially encourages female researchers to apply.

Equally qualified applicants with disabilities will be given preference. Candidates from any nationality can apply.

We are open to discussing options for part-time work or working remotely.


  • Doctoral degree with training or experience in machine learning (ideally as applied to computer vision tasks)
  • Strong coding skills in Python, or other statistical software
  • Good communication skills in English (knowledge of German is not necessary)
  • We offer

  • Target-oriented individual further education and training opportunities
  • Targeted training on the job
  • Ticket for public transport
  • Possibility of child care (crèche and kindergarten) as well as subsidy for holiday care for school children
  • Active health promotion
  • Company pension scheme
  • Access to the university library and other university facilities (e.g. university sports)
  • Contact & Application Please apply by sending a CV to Pascal Geldsetzer at . A cover letter is not required. There is no specific deadline for the application we hire on an ongoing basis.


    Applications will be accepted via e-mail.

    Universitätsklinikum Heidelberg

    Heidelberg Institute of Global Health

    Im Neuenheimer Feld 130.3

    69120 Heidelberg

    Tel. : +49 6221 56-5040

    Published : 29.03.2022

    Wir stehen für Chancengleichheit. Schwerbehinderte werden bei gleicher Eignung vorrangig eingestellt. Das Universitätsklinikum strebt eine generelle Erhöhung des Frauenanteils in allen Bereichen und Positionen an, in denen Frauen unterrepräsentiert sind.

    Qualifizierte Frauen sind daher besonders aufgefordert, sich zu bewerben. Vollzeitstellen sind grundsätzlich teilbar, soweit dienstliche oder rechtliche Gründe nicht entgegenstehen.

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