Job
- Level
- Experienced
- Job Field
- Software, Data
- Employment Type
- Part Time/Full Time
- Contract Type
- Temporary employment
- Salary
- 53.000 to 77.000€ Gross/Year
- Location
- Jena
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop AI methods, integrate them into existing systems, and evaluate their application for analyzing collection-based data in interdisciplinary projects.
Job Technologies
Your role in the team
- 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.
- Work in team projects
- Independent analysis and solution of problems, utilizing existing methods and literature in computer vision and machine learning
- Development and implementation of own and team member's ideas and approaches for novel analysis methods of collection-based data
- Systematic analysis, evaluation and comparison of implemented methods
- Development of deployable ML applications based on methods developed in the group for demo purposes and end-users
- Co-development, extension and curation of joint codebases
- Development of automated workflows for the digitization process and the integration of digitized data in established databases
- Curation and archiving of collection-based image- and text-datasets
- Communication with related Senckenberg groups for integrating our work in the Senckenberg environment
- Support of the group in outreach events
- Supporting administration and maintenance of the institute's server infrastructure
This text has been machine translated. Show original
Our expectations of you
Education
- Bachelor's or Master's Degree in Computer Science or related disciplines
Qualifications
- Good written and oral skills in English & German
- Good organizational abilities, reliability and efficiency
- An open mind-set, curiosity and the desire to learn new technologies
- A collaborative attitude and good communication skills
Experience
- Experience with the implementation of machine learning/deep learning, ideally computer vision approaches and pipelines
- Experience with Large Language Models and APIs
- Experience with 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)
- Desirable skills include experience with computing on clusters, databases and web security, server administration or administration tools, Docker, CI/CD
This text has been machine translated. Show original
What we offer
- 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 at 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
- Flexible working hours
- Mobile working options
- Employee ID card with free admission to the Senckenberg museums
- Annual special payment
- Collectively agreed vacation entitlement
- Company pension plan (ZVK)
This text has been machine translated. Show original
Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Senckenberg Gesellschaft für Naturforschung (SGN), Frankfurt am Main
Die Senckenberg Gesellschaft für Naturforschung (SGN) wurde 1817 gegründet und zählt zu den wichtigsten Forschungseinrichtungen rund um die biologische Vielfalt.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Science, Research
- Salary
- 53.000 to 77.000€ Gross/Year
- Location
- Jena
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
