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POSTDOCTORAL SCIENTIST: BIOINFORMATICS FOR SINGLE-CELL MULTI-OMICS DATA INTEGRATION

03 February 2021

Home Jobs POSTDOCTORAL SCIENTIST: BIOINFORMATICS FOR SINGLE-CELL MULTI-OMICS DATA INTEGRATION

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Interested?

For more information please contact Prof. dr. Thierry Voet, mail: thierry.voet@kuleuven.be or dr. Gregory Maes, mail: gregory.maes@kuleuven.be.You can apply for this job no later than March 01, 2021 via the online application tool

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-2021-111)

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Apply before 01 March 2021

A postdoctoral position is available for a computational biologist at the Center of Human Genetics, KU Leuven in the laboratory 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 ageing and 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, ageing and disease biology. We use robotic and microfluidics assays that process hundreds to thousands of cells in parallel, innovative computational approaches, and are a pioneer in multi-omics measurements from the same cell. You will play a key role in the establishment of innovative analytical pipelines for single-cell multi-omics, data analysis and interpretation. The team also contributes to leading large-scale international communities such as the Human Cell Atlas, the Gut Cell Atlas and the LifeTime initiative.

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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, 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 skills. Given that the field is rapidly advancing, being motivated to learn and keep track of state-of-the-art analysis methods will be required. High accuracy in work, close coordination and effective communication with other team members and teams will be critical to meet the goals of key biological projects.

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 molecular genetics;genomics, epigenomics, transcriptomics and/or next-generation sequencing technologies.
  • 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.

Additional desirable skills and experience

  • 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.