POST-DOC RESEARCHER IN MULTI-OMICS DATA ANALYSIS

Institute for Biomedicine The Institute for Biomedicine, located at Bolzano's NOI Techpark, is a key component of Eurac Research, dedicated to improving health through precision prevention research.
This interdisciplinary effort seeks to predict, slow or preempt illness progression by understanding genetic, biological, environmental, and lifestyle factors.
Utilizing a decade-long population study in collaboration with the South Tyrolean Healthcare Service, the institute offers access to extensive data and biological materials suitable for such research.
With a focus on neurological, cardiovascular, and metabolic health, the team employs state-of-the-art labs and innovative data science to span the full translational research cycle, from data generation to potential clinical application The Institute for Biomedicine at Eurac Research is seeking a highly motivated researcher to join the Computational Genomics Group, to work on the DyHealthNet project.
DyHealthNet is a DFG-funded research project run by FAU (Biomedical Network Science Lab), TUM (Big Data in Biomedicine Group), Eurac Research (Institute for Biomedicine), and UNIBZ (Database Systems Group).
In DyHealthNet, we are developing a network-based software platform for dynamic and explorative analysis of the cohort data from our Cooperative Health Research in South Tyrol (CHRIS) study.
Tasks.
Prepare data, conduct GWAS and WES association analyses.
Define and support the integration of analysis workflows considering the multi-omics data available in CHRIS.
Implement novel algorithms and/or workflows to accelerate data analysis and to support integrative data models.
Coordinate analyses and collaborate with project partner.
Evaluate the developed software platform by analyzing case studies and propose improvements.
Dissemination of scientific results through conference contributions and scientific publications.
Requirements.
PhD within relevant field of research (Bioinformatics, Biostatistics, Computational Biology).
Experience in large scale data handling and processing, including statistical data analysis and machine learning.
Experience in R and/or Python and/or Nextflow software development in a Linux environment.
Experience analyzing data and deploying applications in High-Performance Computing (HPC) systems.
Proficiency in version control systems (GitHub) Experience in the biomedical field, e.
., in genome-wide association studies or proteomics is preferred.
Proactivity and ability to solve problems independently.
Ability to work in a distributed multi-disciplinary research environment.
Excellent written and oral communication skills in English.
We offer.
A collaborative work environment with multidisciplinary teams of experts from different fields of biomedical research.
Access to cutting-edge omics and health data and computational resources.
Attractive living and working conditions.
How to apply.
nterested candidates should submit their application (CV, cover letter and further relevant documents) by .
The project " DyHealthNet" (CUP.
I53C) has been funded by the Autonomous Province of Bolzano/ Bozen South Tyrol and the DFG in the framework of the Programme Joint Projects "Progetti di cooperazione internazionale" - Alto Adige-Germania (DFG).