Postdoctoral scientist: Bioinformatics for single-cell multi-omics data integration

     
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WorkplaceLeuven, Flemish Region, Belgium
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Position

Description

Postdoctoral scientist: Bioinformatics for single-cell multi-omics data integration

Exciting opportunity for state-of-the-art research in single cell genomics

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 various biological domains ranging from human development to ageing to disease studies. 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. 

Core accountabilities:

  • Develop and establish computational analysis methods for single-cell genomic, epigenomic (DNA methylation, open chromatin) and transcriptomic data integration methods.
  • Lead in the experimental design, data analysis and interpretation of large-scale single-cell sequencing projects, and coordinate with experimental biologists. 
  • To be co-responsible for successful completion of projects, and play a key role in the publication of the results.
  • Manage existing and develop new collaborations and relationships internal and external to KU Leuven. 
  • Report and communicate on progress in meetings.
  • Train multidisciplinary team members in the usage of computational analysis methods. You will co-supervise PhD and Master thesis students.


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 (statistical, machine learning) 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.

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 analyses 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.

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 analyses 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.

MSc in Bioinformatics, Biostatistics, Artificial Intelligence, Computer Science or other relevant degree (e.g. Biochemistry, Bioscience Engineering) with a Ph.D.in a relevant subject, e.g. Computational Biology, Functional Genomics, Genomics, Computer Science, Mathematics, Biophysics.

Essential knowledge, skills, and experience required:

  • Evidence for productivity in a research setting such as publications, patents, etc.
  • Ability to work independently and as a team member.
  • Ability to be inventive and to present novel ideas in method development, data analysis and interpretation.
  • High level communication skills that enable you to evoke complex requirements from, and convey complex information to, individuals with different levels of technical knowledge.
  • Excellent critical and problem-solving skills.
  • Knowledge of human molecular genetics; genomics, epigenomics, transcriptomics and/or next-generation sequencing technologies.
  • Strong proficiency in statistical modelling, particularly Bayesian modelling (using STAN and/or PyMC). 
  • Proficiency in R and Python script programming languages.
  • Working proficiency in UNIX/Linux.
  • Extensive experience and in-depth knowledge of bioinformatics approaches for DNA and/or RNA next-generation sequence analyses.
  • Motivation and ambition to make a personal contribution to single-cell omics research.


Additional desirable skills and experience:

  • Experience with single-cell multi-omics analytics and computational method development in the area.
  • A strong scientific publication record.
  • Experience with large-scale computational analysis; running software on a high-performance computing cluster or cloud environment.
  • Experience in creating and using containerized computing environments (e.g using Docker, Singularity).
  • Experience in creating and implementing complex data workflows (e.g. using Snakemake, Nextflow).
  • Experience using classical and/or deep machine learning methods (using TensorFlow/Keras).



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 [at] kuleuven[.]be.

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In your application, please refer to myScience.be and reference JobID 2664.

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