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Postdoctoral Researcher – AI-based Multi-Omics in Computational Biomedicine(m/w/x)
AI model development using graph neural networks for multi-omics analysis in a clinical research setting. 1-3 years postdoctoral research experience and publication track record essential. Public sector collective agreement, state-of-the-art computational infrastructure.
Requirements
- PhD in Bioinformatics, Computational Biology, Data Science, or related field
- Strong background in machine learning and statistical modeling
- 1–3 years of postdoctoral or equivalent research experience
- Track record of publications in peer-reviewed journals
- Experience with multi-omics data integration
- Proficiency in Python/R and deep learning frameworks
- Strong interest in translational biomedical research
Tasks
- Develop AI models for integrative multi-omics analysis
- Apply graph neural networks and variational autoencoders
- Construct molecular interaction networks across various data types
- Analyze transcriptomic, proteomic, and metabolomic data
- Perform biomarker discovery and simulation-based perturbation analyses
- Collaborate with clinicians and experimental scientists
- Publish research findings in high-impact journals
- Contribute to open-source software development
Work Experience
- 1 - 3 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- Python
- R
- PyTorch
- TensorFlow
Benefits
Startup Environment
- Interdisciplinary research environment
Modern Equipment
- State-of-the-art computational infrastructure
Informal Culture
- National and international collaboration
- Motivated and open-minded team
Job Security
- Secure and stable position
Retirement Plans
- Additional pension coverage (VBL)
Diverse Work
- Interesting and varied position
Mentorship & Coaching
- Structured onboarding
Learning & Development
- Qualified training
Healthcare & Fitness
- Comprehensive health promotion program
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Postdoctoral Researcher – AI-based Multi-Omics in Computational Biomedicine(m/w/x)
AI model development using graph neural networks for multi-omics analysis in a clinical research setting. 1-3 years postdoctoral research experience and publication track record essential. Public sector collective agreement, state-of-the-art computational infrastructure.
Requirements
- PhD in Bioinformatics, Computational Biology, Data Science, or related field
- Strong background in machine learning and statistical modeling
- 1–3 years of postdoctoral or equivalent research experience
- Track record of publications in peer-reviewed journals
- Experience with multi-omics data integration
- Proficiency in Python/R and deep learning frameworks
- Strong interest in translational biomedical research
Tasks
- Develop AI models for integrative multi-omics analysis
- Apply graph neural networks and variational autoencoders
- Construct molecular interaction networks across various data types
- Analyze transcriptomic, proteomic, and metabolomic data
- Perform biomarker discovery and simulation-based perturbation analyses
- Collaborate with clinicians and experimental scientists
- Publish research findings in high-impact journals
- Contribute to open-source software development
Work Experience
- 1 - 3 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- Python
- R
- PyTorch
- TensorFlow
Benefits
Startup Environment
- Interdisciplinary research environment
Modern Equipment
- State-of-the-art computational infrastructure
Informal Culture
- National and international collaboration
- Motivated and open-minded team
Job Security
- Secure and stable position
Retirement Plans
- Additional pension coverage (VBL)
Diverse Work
- Interesting and varied position
Mentorship & Coaching
- Structured onboarding
Learning & Development
- Qualified training
Healthcare & Fitness
- Comprehensive health promotion program
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Universitätsklinikum Erlangen
Industry
Healthcare
Description
Das Unternehmen bietet Patientenversorgung auf höchstem Niveau, ausgezeichnete Forschung und Lehre sowie modernste Medizin und Diagnostik.
Not a perfect match?
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