Wissenschaftliche Hilfskraft am HIGH - Heidelberg Institute of Global Health (m/f/d)

The Heidelberg Institute of Global Health (HIGH) is looking for a HiWi to assist with a project that will use convolutional neural networks in satellite imagery to predict global health indicators. Under the guidance of Dr. Pascal Geldsetzer and other researchers at Heidelberg and Stanford University, the student will help with assembling the dataset for analysis and building the convolutional neural networks. The broad aim of these analyses is to test whether satellite imagery could be used to monitor important health indicators in low- and middle-income countries at a highly granular geographic and temporal level. The number of hours per months is negotiable. Working remotely is possible.

  • Job-ID: V000010075
  • Field of application: Heidelberg Institute of Global Health
  • Location: Heidelberg
  • Start date: as soon as possible
  • Job Category: Science and teaching
  • Working hours: Part time (85 Hours/Month)
  • Published: 10.11.2023
  • Limitation:Temporary
  • Contract:Sonstige

Requirements and Offer

  • A university degree with quantitative training or quantitative research experience. A degree in a health-related subject is not required to apply
  • Experience with machine learning, particularly in the area of computer vision and convolutional neural networks, is a plus but not a requirement
  • Experience coding in Python or R
  • Good communication skills in English (knowledge of German is not necessary)

A medical background is not needed. The HiWi will be an author on publications to which he/she has contributed.

Contact & Application

Interested candidates should send a CV to Dr. Pascal Geldsetzer at pascal.geldsetzer@uni-heidelberg.de. A cover letter is not required.

Heidelberg Institute of Global Health
Dr. Pascal Geldsetzer
Im Neuenheimer Feld 130.3
69120 Heidelberg

Please note that the UKHD is subject to the provisions of the Infection Protection Act. Therefore, valid proof of measles immunity is required for all persons employed at the UKHD.

We stand for equal opportunities. Severely disabled persons are given priority in the case of equal suitability. The University Hospital aims to generally increase the proportion of women in all areas and positions in which women are underrepresented. Qualified women are therefore particularly encouraged to apply. Full-time positions are generally divisible, unless there are official or legal reasons to the contrary.