Postdoc (m/f/d) for AI-driven Method Development for Collection-based Research
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.
The selected candidate will research novel methods in the areas of foundation models, few- and zero-shot methods and domain generalization in established team projects and novel projects in order to advance collection-based research.•
- Work in (team) projects by contributing, co-developing, executing, implementing and evaluating ideas for novel AI-driven image and data analysis approaches for collection data •
- Establishment of own projects, research questions and approaches for image and data analysis of collection data with focus on broadly applicable methods able to deal with little available data (e.g., zero-shot, few-shot or weakly supervised approaches and foundation models) •
- Publication and presentation of research results in high-ranked machine learning, computer vision and interdisciplinary venues •
- Curation and archiving of datasets •
- Keeping up with current developments in computer vision and machine learning research •
- Support of funding acquisition and establishment of the new group at Senckenberg, including participation in outreach events •
- Advising of colleagues and students, including supervision of bachelor’s and master’s theses
Your Profile•
- A doctoral degree (or in the stage of its finalization) in Computer Science or a related subject with a focus on computer vision and/or deep learning, ideally with interdisciplinary experience, or a doctoral degree (or in the stage of its finalization) in Biology with strong computer vision and deep learning background (application or research)
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- Experience with: Current methods, tools, languages and frameworks in computer vision and deep learning (e.g., Linux, Bash, Python, Pytorch, Gradio, Numpy, Pandas, Huggingface, Ollama) -LLMs and foundation models in general •
- Good organizational abilities, reliability and efficiency •
- An open mind-set, curiosity and a strong motivation to excel in science •
- A collaborative attitude and good communication skills •
- Excellent written and oral communication and presentation skills in English
Desirable Skills:•
- German language skills •
- Experience with computing on clusters •
- Experience with funding-acquisition
We offer
Location: Jena, Germany Employment scope: Full-time (40 hours/ week) / part-time options are available Type of contract: The contract shall start at the earliest possible date. The position is limited to 2 years Remuneration: Collective agreement of the German Länder, TV-L E 13•
- An attractive, responsible and challenging position in a globally recognized research institution with motivated and professional colleagues •
- A vibrant, international team of scientists in Jena and all of Senckenberg with collection-based research programs, focusing on understanding the Anthropocene Biodiversity Change •
- Excellent infrastructure and collaboration opportunities at SIP embedded in a lively research environment in Senckenberg and the Friedrich Schiller University Jena •
- Opportunities to participate in teaching and outreach activities, e.g. at Friedrich Schiller University Jena •
- Flexible working hours – mobile working options – employee ID card with free admis-sion to the Senckenberg museums – annual special payment – collectively agreed vacation entitlement – company pension plan (ZVK)