Postdoc (m/f/d) Data Science / Bioinformatics

Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena

The Leibniz Chair research group of Prof. Alessandro Cellerino (SNS Pisa/FLI) is looking for a postdoctoral researcher position in Data Science/Bioinformatics to analyze multiomics datasets in animal models (killifish) and humans and apply machine learning algorithms to derive novel biomarkers of healthy ageing/longevity.

Research focus of the Lab:

Prof. Alessandro Cellerino has a professorship at SNS PISA, Italy and is Leibniz Chair for Biology of Ageing at the Leibniz Institute on Aging - Fritz Lipmann Institute (FLI). The group has a tradition of performing experimental studies on aging in the killifish (Nothobranchius furzeri) using genetic and non-genetic interventions focusing on neurobiology and life-extension and in the generation analysis and validation of high-throughput molecular profiling data.

The position is financed by a three-year DFG project “Multiomic longitudinal analysis of lifespan predictors”.

The overall focus of the project is generate and validate novel aging biomarkers using artificial intelligence. : 1. to integrate proprietary longitudinal and cross-sectional killifish data with public human datasets to develop novel aging biomarkers using advanced AI methods and 2. To validate these biomarkers in datasets of animals subject to experimental life-extension. For a recent example, see Ferrari et al, BioRxiV doi.org/10.1101/2022.11.26.517610.

Tasks and Challenges:

The candidate will work preferentially on analysis of proprietary longitudinal and cross-sectional multiomics datasets of killifish aging and public human aging datasets but will have the flexibility to develop their own project and/or work on a projects previously agreed upon with the group leader.

The candidate will be expected to assume the leading role in the dissemination of the results of the projects by presenting the results at conferences, writing publications and in any other form deemed appropriate.

The candidate will be expected to integrate and work harmoniously in a research group that performs extensive experimental activity and to develop collaborative projects with the Institute and with external partners.


  • PhD in computational or experimental biology, data science, physics, mathematics, statistics or related fields
  • Experience with machine learning and deep learning algorithms and deep knowledge of statistics
  • Advanced programming skills and experience in R and Python
  • Genuine interested in becoming part of the community active in the field of longevity science and technologies (prior experience in the field is not required!)
  • Experience with analysis of high-dimensional biological data is preferred

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