PostDoc position in Machine learning tools to combine sequence and biologically heterogeneous data (Ref. 6/2017)

Deadline:
31/08/2017
Centre / Institution:
Centre for Research in Agricultural Genomics
Bioinformatics expertise:
Agrigenomics, Algorithmics, Biostatistics, Computational Genomics, Genetic Variation Analysis, Integrative Bioinformatics, Population Genetics, Systems Biology and Networks
Keywords:
Machine learning, deep learning, phenotype

Job description

Postdoc position. Big data are characterized not only by their size but also by their heterogeneity and noisiness. These features apply in particular to genomic data: their size has been increasing exponentially with the advent of new sequencing technologies, but also their complexity. We aim at combining several available sources of information, not only the phenotypes and sequence data, but also, e.g., annotation features or metabolic pathways. An important goal is not only to provide efficient predictors but also tools to biologically interpret the results. We will explore machine learning tools such as ensemble methods or deep learning to investigate two main problems (i) genomic prediction, and (ii) inference of selective sweeps. 

Group description
The Numerical Genomics group (http://bioinformatics.cragenomica.es/numgenomics) at Centre for Research in Agricultural Genomics (CRAG) is primarily interested in the use of high throughput sequencing technology (NGS) for population and statistical genomics. Topics of particular interest are studying the footprint of domestication and artificial selection and the use of sequence for genomic selection. CRAG  was recently awarded a Severo Ochoa project for excellence centres in Spain. This project will be carried out in cooperation with international and national groups with a long experience in machine learning that complement our expertise.

Desired skills and expertise

We are looking for a PhD with a computational profile and an interest in biological applications. 
Required

  • Programming ability and experience in python
  • Quantitative and/or population genetics background

Valued

  • Experience in machine learning area

Contract duration and other benefits

We offer a 22 month year postdoc contract (extendable up to three years if funding is available).

Required information and contact

Interested candidates, please submit: Send CV, motivation letter and email of two contact persons.

Deadline: Applications will be accepted and the position will remain open until it is filled.