Expert in Machine Learning: Multi-Omics Factor Analysis in Biological and Biomedical Research
Location: Heidelberg, Germany
Staff Category: Staff Member
Contract Duration: 3 years
Grading: 5 or 6, depending on experiece and qualifications
Closing Date: 16 June 2019
Reference Number: HD01466
The research group of Wolfgang Huber at EMBL (Heidelberg) works on statistical computing for biology and biomedicine research. The interdisciplinary team engages in theoretical method development, translation into effective software, and scientific applications in collaboration with researchers in systems genetics and precision medicine.

Your role

You will develop methods for finding low-dimensional explanations in high-dimensional biological data. Biological systems are now being studied at multiple levels (DNA sequence, chromatin plasticity, transcriptome, proteome, metabolome, imaging-based morphometry, etc.), increasingly at single-cell resolution. Such data, which often comprise millions of features per observational unit, have a wide range of applications in basic biology and in biomedicine, e.g. to study cell fate decisions or disease heterogeneity. You will be working on the most fundamental step in their analysis: finding and understanding the most important patterns, such as latent factors, clusters, gradients, smooth manifolds, graphs, etc. that are hidden in the high-dimensional data. The learning tasks comprise unsupervised, supervised and hybrid setups.

The scope of this research covers mathematical theory development, implementation into high-quality scientific software, and application to biological / medical discovery in collaboration with domain experts, and we are interested in candidates covering one or several of these.

Relevant publications:
  • Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets. Argelaguet, Ricard, Velten, B., et al. Molecular Systems Biology (2018), DOI 10.15252/msb.20178124
  • Orchestrating high-throughput genomic analysis with Bioconductor. Huber, W., et al. Nature Methods (2015), DOI 10.1038/nmeth.3252

You have

  • a PhD or equivalent qualification in a quantitative science (mathematics, statistics, physics, computer science, computational biology)
  • excellent foundations in probability theory, statistics, linear algebra and differential geometry
  • experience in statistical data analysis and a solid understanding of programming concepts and multiple languages including R and Python
You are excited by making or contributing to biological discoveries, and you are interested in understanding the modern biotechnologies that enable us to make the measurements with which you work.

You might also have

Experience with biological or biomedical data is a plus.

Why join us

EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation with a very collegial and family friendly working environment. The remuneration package comprises a competitive salary, a comprehensive pension scheme, medical, educational and other social benefits, as well as financial support for relocation and installation, including your family and the availability of an excellent child care facility on campus.

What else do I need to know

We are Europe’s flagship research laboratory for the life sciences – an intergovernmental organisation performing scientific research in disciplines including molecular biology, physics, chemistry and computer science. We are an international, innovative and interdisciplinary laboratory with more than 1600 employees from many nations, operating across six sites, in Heidelberg (HQ), Barcelona, Hinxton near Cambridge, Hamburg, Grenoble and Rome.

Our mission is to offer vital services in training scientists, students and visitors at all levels; to develop new instruments and methods in the life sciences and actively engage in technology transfer activities, and to integrate European life science research.

Please note that appointments on fixed term contracts can be renewed, depending on circumstances at the time of the review.