CfDNA Postdoctoral Fellow​/Senior Postdoctoral Fellow in statistical genomics

## cfDNA Postdoctoral Fellow / Senior Postdoctoral Fellow in statistical genomics

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Hinxton, Cambridgeshire:
Full time:
Posted 4 Days Ago:
JR104056

Do you want to help us improve human health and understand life on Earth? Make your mark by shaping the future to enable or deliver life-changing science to solve some of humanity’s greatest challenges.

We are seeking a highly motivated and creative Postdoctoral Fellow or Senior Postdoctoral Fellow to join the Martin group at the Wellcome Sanger Institute, to develop and apply statistical and machine learning methods to cell-free DNA from pregnant women and people.  
** About the group:
** The Martin group works on the genetic basis of rare and common disease, using large-scale human genetic datasets with rich linkage to electronic health records and questionnaires. Over the last few years, we have had a particular emphasis on the genetics of neurodevelopmental disorders and related traits, the genetics of complex disease in populations with high levels of consanguinity, and factors influencing germline mutation rates.  

The group is now opening new research directions involving genomics and multi-omics in very early life. Most conditions in the earliest stages of life remain untouched by large-scale genomics, and molecular predictors that could guide clinical management are urgently needed. We are building a programme spanning a clinical continuum from pregnancy loss, through fetal growth restriction, to complications of premature birth.

This includes large-scale sequencing of cell-free DNA (cfDNA) from pregnant women and people to identify monogenic causes of pregnancy loss and identify biomarkers for fetal growth restriction, as well as genetic and multi-omic studies of neonatal conditions using nationwide dried blood spots.  
** What you'll be doing:
** This particular role is focused on cell-free DNA (cfDNA) from pregnant women and people. cfDNA in maternal plasma is a mixture of maternal and fetal (placental) molecules, and offers a route to studying fetal genomes and placental biology at a scale that is impossible with fetal tissue. Possible projects include:
* Developing new statistical and deep learning methods for calling fetal and maternal genotypes from high-coverage sequence data on cfDNA, and for discovering new Mendelian disease genes using the resulting data. These methods will then be applied to study pregnancy complications in large samples.
* Developing biomarkers for pregnancy complications from methylation-aware whole genome sequence data on cfDNA, including methods development to incorporate both epigenetic and genetic information in the same assay. You will have the opportunity to collaborate with groups at the Norwegian Institute of Public Health (Siri Eldevik Håberg), the University of Helsinki (Simone Rubinacci) and elsewhere.  
*
* About you:

** We are recruiting at two levels:
Postdoctoral Fellow and Senior Postdoctoral Fellow. In both cases, you will have a demonstrable background in statistics or statistical genetics.

Experience of working with cfDNA is highly desirable but not essential. The role would particularly suit if you have previously worked on methods for somatic variant calling, or for phasing and imputation from low-coverage sequence data.

You would also bring excellent software development skills, since the methods developed here are intended to be applied across several large cohorts and shared with collaborators. The Senior Postdoctoral Fellow role is intended for someone with particularly strong experience in these areas who is ready to work with a high degree of independence, to shape the direction of the methods development, to lead collaborations and to mentor more junior members of the group.

You will be considered at the level that best matches your experience, so please apply even if you are unsure which position fits. Prospective candidates are welcome to contact Hilary Martin () with informal queries before deciding whether to apply.  
** Essential

Skills:

*** PhD in a relevant area (statistics, statistical genetics, genetics, genomics, bioinformatics, machine learning or similar)
* Strong background in statistics or statistical genetics, including the ability to develop, implement and benchmark new statistical methods
* Experience working with raw sequence data (alignments, variant calling, quality control)
* Experience analysing large-scale human genetic or genomic data
* Full working proficiency in Python and/or R, and Unix/Linux
*…