Institute of Computer Science - Hannover, Deutschland - Universität Osnabrück

Universität Osnabrück

Geprüftes Unternehmen

Hannover, Deutschland

vor 3 Wochen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

The DFG-funded Research Training Group "Ecological Regime Shifts and Systemic Risk in Coupled Social-Ecological Systems" (ECORISK) deals with the causes of ecological regime shifts and their potential consequences in social-ecological systems in an interdisciplinary approach.

ECORISK aims at training a new generation of innovative scientists capable of dealing with complex sustainability challenges. It brings together perspectives from behavioral economics, ecological modeling, environmental systems science, geography, geoinformatics, political science, and sociology.

ECORISK is located at Osnabrück University, which is renowned for its outstanding interdisciplinary research and embedded in a city with an excellent quality of life.

In the subproject _"Mapping land management archetypes by multisensor remote sensing data and machine learning"_ at the Institute of Computer Science, a position as

(Pay grade 13 TV-L, 75%):

is to be filled on a fixed-term basis until September 30, 2027, starting on October 1, 2024.

Your Duties:

- research work in the above-mentioned subproject; analyzing large-scale remote sensing data (multispectral and SAR) by deep learning
- peer-review publication of research results, as basis for your own academic qualification in the form of a doctoral degree
- participation in and contribution to the events of the Research Training Group

Requirements:

- an above-average University degree (MSc or equivalent) in the field of Geomatics or a related discipline, focusing on (environmental) remote sensing
- sound background in remote sensing
- experience in remote sensing image analysis with machine learning (proofed by e.g., study projects, Master thesis)
- programming skills in Python (proofed by e.g., study projects, Master thesis)
- solid knowledge of English

Additional Qualifications:

- knowledge in deep learning, Tensorflow, PyTorch
- knowledge in German
- experience in interdisciplinary collaborations

We offer:

Participation in an exciting and highly topical research project
Tailored training opportunities
Flexible working hours and excellent facilities

Osnabrück University is a family-friendly university and is committed to helping working/studying parents balance their family and working lives.

Osnabrück University seeks to guarantee equality of opportunity for women and men and strives to correct any gender imbalance in its schools and departments.