Wissenschaftliche Hilfskraft am HIGH - Heidelberg Institute of Global Health

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:

29.03.2024

Limitation:

Temporary

Contract:

Sonstige
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.
Interested candidates should send a CV to Dr. Pascal Geldsetzer at 
. A cover letter is not required.
Heidelberg Institute of Global Health
Dr. Pascal Geldsetzer
Im Neuenheimer Feld 130.3
69120 Heidelberg
Note: The UKHD is subject to the provisions of the Infektionsschutzgesetz. Therefore, a valid measles immunity certificate is required for all persons employed at the UKHD.

The UKHD embraces diversity and values diversity.
Regardless of age, gender, sexual identity, disability, origin or religion, we offer everyone the same opportunities. If one gender is underrepresented in a particular area, we place particular emphasis on counteracting this imbalance. If they have the same aptitude, qualifications and professional performance, we give priority to people with severe disabilities when considering them for vacancies.

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