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Job-ID
22/43
Application by 01.02.2023

The Leibniz Institute on Aging - Fritz Lipmann Institute (FLI) in Jena is a federal and state government-funded research institute and member of the Leibniz Association (Leibniz-Gemeinschaft). FLI’ s internationally visible and highly competitive research is focused on understanding the mechanisms of aging and associated age-related diseases. Scientists from over 40 countries are currently investigating the molecular mechanisms of aging and the occurrence of age-related diseases. Our aim is to create the basis for new approaches in medicine as a way to improve the health of the elderly (www.leibniz-fli.de).

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.

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

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.
  • 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.
  • 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

      Requirements:

      • 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

      We offer:

      • A position in a well-equipped and motivated group that bridges experimental- and computational research
      • Access to multiple state-of-the-art facilities. Our work is embedded in the Beutenberg Campus, an interdisciplinary base for innovative research.
      • A position integrated in the FLI PostDoc Network. The Network promotes interdisciplinary collaborations involving clinician scientists, basic scientists and bioinformaticians and supports career development and postdoctoral training courses.
      • The contract conditions and the salary will be according to the collective labour agreement for public service employees of the federal states of Germany (TV-L E13) for 2 years initially, with a possibility of extension.
      • Flexible working time, a family friendly working environment including support for child care solutions and dual career.

      Application:

      Please apply online through the FLI application portal by 01.02.2023.





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