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Leibniz Centre for Agricultural Landscape Research

Postdoctoral Researcher in AI, Digital Phenotyping and Plant Genetics for Climate-Resilient Agriculture Lithuanian Research Centre for Agriculture and Forestry in Germany

Degree Level

Postdoc

Field of study

Computer Science

Funding

Approximately €2,600 per month after taxes, with opportunities for additional income through funded projects. The position is offered for two years with a possibility of extension.

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Country

Germany

University

Leibniz Centre for Agricultural Landscape Research

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Keywords

Computer Science
Environmental Science
Agriculture
Biology
Statistical Analysis
Plant Breeding
Artificial Intelligence
Python Programming
3d Imaging
Hyperspectral Imaging
Statistics
ML

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About this position

We’re hiring a Postdoctoral Researcher at the Lithuanian Research Centre for Agriculture and Forestry (LAMMC), Laboratory of Genetics and Physiology, to work at the intersection of AI, digital phenotyping, plant genetics, and climate-resilient agriculture.

The project focuses on developing methods to analyse UAV and ground-based RGB, multispectral, hyperspectral, and 3D imagery, while integrating genomic, transcriptomic, and agronomic data to better understand crop growth, stress responses, and yield potential.

Ideal candidates should hold a relevant PhD (awarded within the past seven years) and bring strong Python/R and statistical or machine learning skills. Experience with genomic/transcriptomic datasets and spectral sensing or high-throughput phenotyping is specifically highlighted.

The position is based in Akademija, Kėdainiai district, Lithuania. Funding is approximately €2,600 per month after taxes, with opportunities for additional income through funded projects. The appointment lasts two years with a possible extension.

To apply, send a CV, a brief motivation letter, and the contact details of two referees to [email protected].

Funding details

Approximately €2,600 per month after taxes, with opportunities for additional income through funded projects. The position is offered for two years with a possibility of extension.

What's required

Applicants should have a relevant PhD, with the PhD awarded within the past seven years. Strong Python and/or R skills and statistical or machine learning experience are required. Experience with genomic and transcriptomic data and spectral sensing or high-throughput phenotyping is expected.

How to apply

Send your CV, a brief motivation letter, and contact details for two referees to the listed email address.

More information can be found here

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