Abrar Admin

Senckenberg Gesellschaft für Naturforschung

<div>Senckenberg &ndash; Leibniz Institution for Biodiversity and Earth System Research (SGN), headquartered in Frankfurt am Main, is seeking to fill the following position in the Research Group Digital Collectomics at the Senckenberg Institute for Plant Form and Function starting as soon as possible<h2 class="jobSectionHeader"> 
AI Engineer (m/f/d) for Method Development and
</h2><h2 class="jobSectionHeader">Digitization for Collection-based Research</h2>
Location: Jena (Thuringia, Germany)
Employment scope: Full-time (40 hours per week) / part-time options are available
Type of contract: The contract shall start at the earliest possible date and is limited to 2 years
Remuneration: Collective agreement of the German L&auml;nder, TV-L E 11
The Senckenberg Society for Nature Research is a member of the Leibniz Association and has been investigating the &ldquo;Earth System&rdquo; worldwide for more than 200 years, examining the past, analysing the present, and developing projections for the future.
We conduct integrative geobiodiversity research with the aim of understanding nature in all its complexity and diversity in order to preserve it as the foundation of life for future generations and to ensure its sustainable use. Across eight institutes and five research stations throughout Germany, scientists from more than 40 countries conduct research at the highest international level.
The Senckenberg Institute for Plant Form and Function (SIP) at Friedrich Schiller University Jena (FSU) is the eighth and most recently founded Senckenberg institute. Located in the vibrant university city of Jena in Thuringia and forming part of an international network, it brings together the renowned Herbarium Haussknecht with cutting-edge research on biodiversity change in the Anthropocene.
The Junior Research Group Digital Collectomics deals with the development of automated methods revolving around the extraction of information from collections, with a strong focus on herbaria, as well as the digitization process and public display thereof.
We leverage the latest developments in computer vision and AI research to create broadly applicable methods that can deal with small to no available training data. Therefore, our research focuses primarily on foundation models, few- and zero-shot methods and domain generalization. In interdisciplinary cooperation with the local Herbarium Haussknecht and partners all over Senckenberg, we create cutting-edge approaches for publication in high-ranked computer vision, machine learning and interdisciplinary venues with the ambition to convert the novel methods into directly applicable tools usable in collection-based research at the Senckenberg and beyond.
The selected candidate will employ, adapt and assess methods from the literature in the areas of foundation models, few- and zero-shot methods and domain generalization in established team projects and novel projects, integrate the developed methods into the Senckenberg infrastructure and make developed methods usable for end users.
Your tasks
<ul><li>Work in team projects
</li><li>Independent analysis and solution of problems, utilizing existing methods and literature in computer vision and machine learning
</li><li>Development and implementation of own and team member&rsquo;s ideas and approaches for novel analysis methods of collection-based data</li><li>
Systematic analysis, evaluation and comparison of implemented methods
</li><li>Development of deployable ML-applications based on methods developed in the group for demo purposes and end-users
</li><li>Co-development, extension and curation of joint codebases
</li><li>Development of automated workflows for the digitization process and the integration of digitized data in established databases</li><li>
Curation and archiving of collection-based image- and text-datasets
</li><li>Communication with related Senckenberg groups for integrating our work in the Senckenberg environment
</li><li>Support of the group in outreach events</li><li>
Supporting administration and maintenance of the institute&rsquo;s server infrastructure</li></ul>
Your profile
<ul><li>Bachelor&rsquo;s or Master&rsquo;s Degree in Computer Science or related disciplines
</li><li>Experience with
</li><li>The implementation of machine learning/deep learning, ideally computer vision approaches and pipelines</li><li>
Large Language Models and APIs
</li><li>Current technologies, languages and frameworks for the development and deployment of ML methods (e.g., Linux, Bash, Python, Numpy, Pandas, Pytorch, Gradio, HTML, CSS, Javascript)
</li><li>Good written and oral skills in English &amp; German</li><li>
Good organizational abilities, reliability and efficiency
</li><li>An open mind-set, curiosity and the desire to learn new technologies
</li><li>A collaborative attitude and good communication skills</li></ul>
Advantangeous skills
<ul><li>Experience with computing on clusters
</li><li>Experience with databases and web security
</li><li>Experience with server administration or administration tools
</li><li>Experience with Docker, CI/CD
</li></ul>What you can expect
<ul><li>An attractive, responsible and challenging position in a globally recognized research institution with motivated and professional colleagues</li><li>
A vibrant, international team of scientists in Jena and at Senckenberg with collection-based research programs, focussing on understanding the Anthropocene Biodiversity Change</li><li>
Excellent infrastructure and collaboration opportunities at SIP embedded in a lively research environment in Senckenberg and the Friedrich Schiller University Jena</li><li>
Flexible working hours &ndash; mobile working options &ndash; assistance with child care and care for family members (&bdquo;audit berufundfamilie&ldquo;) &ndash; annual special payment &ndash; collectively agreed vacation entitlement &ndash; company pension plan</li></ul>
Senckenberg is committed to diversity. We benefit from the different expertise, perspectives and personalities of our staff and welcome every application from qualified candidates, irrespective of age, gender, ethnic or cultural origin, religion and ideology, sexual orientation and identity or disability. Applicants with a severe disability will be given special consideration in case of equal suitability. Senckenberg actively supports the compatibility of work and family and places great emphasis on an equal and inclusive work culture.
You would like to apply?

We look forward to receiving your application. Please upload your comprehensive documentation &ndash; consolidated into a single PDF file &ndash; via our online application portal by
02 August 2026.<ul><li>
A letter of motivation highlighting your relevant project experience and your technical expertise,</li><li>
your CV,
</li><li>copies of your (academic) certificates and diplomas</li></ul>
Apply now via: https://senckenberg.career.softgarden.de/
﻿
Please note that interviews are planned to take place from August 25th onwards. We will provide further details in due course.
Join us in advancing ecological research through innovative technology! We look forward to your application!
Contact

Senckenberg Gesellschaft f&uuml;r Naturforschung
Senckenberganlage 25
60325 Frankfurt am Main
For specific questions about this role, please contact Dr. Matthias K&ouml;rschens at matthias.koerschens@senckenberg.de.
For specific questions about the application and selection process, please contact:
recruiting@senckenberg.de
For data protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/
For further information about the Senckenberg Gesellschaft f&uuml;r Naturforschung please visit www.senckenberg.de</div>

AI Engineer (m/f/d) for Method Development and Digitization for Collection-based Research

Join Senckenberg Gesellschaft für Naturforschung and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Senckenberg Gesellschaft für Naturforschung

About Company

AI Engineer (m/f/d) for Method Development and Digitization for Collection-based Research