POSTDOCTORAL SCIENTIST: BIOINFORMATICS FOR SINGLE-CELL MULTI-OMICS RESEARCH IN HUMAN AGING AND PARKINSON’S DISEASE

28 May 2021

Get in touch!

Interested?

For more information please contact Prof. dr. Thierry Voet, mail: thierry.voet@kuleuven.be or Dr. Shinjini Mukherjee, mail: shinjini.mukherjee@kuleuven.be.You can apply for this job no later than June 24, 2021.

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

(ref. BAP-2021-419)

Apply before 24 June 2021

A postdoctoral position is available for a computational biologist at the Center of Human Genetics, KU Leuven in the team of Prof. Thierry Voet. In this position you will be responsible for the development and implementation of data analysis strategies for single-cell multi-omics data integration. You will then also be able to apply these strategies to develop understanding of human aging and disease, in particular Parkinson’s disease. By integrating genomic, transcriptomic and epigenomic highly-dimensional data of individual cells using state-of-the-art statistical models and machine learning strategies we aim to answer key fundamental biological questions with potentially high impact in their respective fields.

The team of Prof. Thierry Voet is a highly multidisciplinary team developing and using cutting-edge molecular biology and computational methods to study single cells, to investigate human development, aging and disease biology. Prof. Thierry Voet is also the director of the newly founded KU Leuven Institute for Single Cell Omics (LISCO), that nucleates interdisciplinary research with a wide range of research groups. The Voet team also contributes to leading large-scale international communities such as the Human Cell Atlas and the Gut Cell Atlas.

Website unit

Responsibilities
  • Develop and establish computational analysis methods for single-cell genomic, epigenomic (DNA methylation, open chromatin) and transcriptomic data integration methods as well as spatial molecular analyses.
  • Lead in the experimental design, data analysis and interpretation of large-scale single-cell multiomics datasets in the context of human aging and Parkinson’s disease, and coordinate with experimental biologists.
  • To play a key role in the publication of the results.
  • Report and communicate on progress in meetings.


Most challenging aspects of the role:Establishing analytical workflows for single-cell (multi)omics measurements requires a high degree of innovative reasoning, in-depth knowledge of and creativity with computational and statistical methods. Strong data interpretation and problem-solving skill

Profile
  • MSc in Bioinformatics, Biostatistics, Artificial Intelligence, Computer Science or other relevant degree e.g. Bioscience Engineering with a Ph.D. in a relevant subject, e.g. Computational Biology, Functional Genomics, Genomics.
  • Motivation and ambition to make a personal contribution to single-cell omics research.
  • Extensive experience and in-depth knowledge of bioinformatics approaches for DNA and/or RNA next-generation sequence analyses.
  • Working proficiency in UNIX/Linux.
  • Proficiency in R, Bash and another script programming language (Python, Perl, Ruby, ...).
  • Knowledge of human genetics; genomics, epigenomics, transcriptomics and next-generation sequencing technologies and data types.
  • Excellent strategic thinking, critical and problem-solving skills.
  • High level communication skills.
  • Ability to be inventive and to present novel ideas in method development, data analysis and interpretation.
  • Ability to work independently and as a team member.


Optional skills and experience with an added value

  • Experience with single-cell and/or spatial multi-omics analytics and computational method development in the area.
  • Experience in statistical modelling, particularly Bayesian modelling (using STAN and/or PyMC).
  • Experience using classical and/or deep machine learning methods (using TensorFlow/Keras).
  • Experience in creating and implementing complex data workflows (e.g. using Snakemake, Nextflow).
  • Experience in creating and using containerized computing environments (e.g using Docker, Singularity).
  • Experience with large-scale computational analysis; running software on a high-performance computing cluster or cloud environment.
  • A strong scientific publication record.
Offer
  • An opportunity to work in a unique professional environment at the most innovative university in Europe: the KU Leuven Health Sciences Campus (Leuven, Belgium), where top researchers and top clinicians meet and collaborate.
  • A chance to contribute to breakthrough research projects and make an impact for people living with brain diseases.
  • A possibility to work independently within a professional research and management team.
  • A full-time extendable position and a competitive salary; the project is for 3 years.