This is an exciting opportunity to work on machine learning approaches to the genetics of neurodevelopmental disorders (NDD) in a joint project in collaboration with a team of Canadian scientists . The project will involve assembling of relevant genomic and genetic data to enable machine learning models to be built to predict genes with a positive or negative effect on specific NDD-relevant behaviours.
Neurodevelopmental disability (NDD) is an umbrella term for a group of disorders including autism, intellectual disability, attention deficit and learning disability. NDD has a very significant impact with a 13 % incidence in the US population. The last decade has seen an explosion in our understanding of the genetic basis of NDD, but targeted, mechanistic, informed treatments are still not available, largely because NDD is highly complex, both in its clinical presentation and genetic etiology. This wide spectrum of phenotype severity is linked in part to complex genetic interactions.
The post will involve use of genomic information and diversity in clinical presentation as a guide to treatment development in NDD. With several large datasets (in Canada and the UK) featuring genomic and phenotypic data, we will use machine learning to identify the features (gene expression, ontology, pathway relationships) that are associated with variation in symptoms (phenotype) severity.
You will:
Identify and organise the genomic data that will be used as features for the machine learning including using ontologies for metadata
Jointly develop machine learning approaches to identify modifiers of genetic effects.
Assess and feedback on the performance of the machine learning models
Contribute to the design and implementation of a project portal to disseminate the model and results.
You have:
PhD in Genetics, Bioinformatics, Computational Biology or a related discipline
Experience in human genetics or genomics data analysis, and proficient with for instance R and/or python
Must be able to communicate analysis and results clearly to a diverse audience
Must be able to identify and clearly express limitations or pitfalls in potential approaches
You might also have:
Experience in Machine Learning in a biological context
Experience in an area related to drug discovery would be an advantage
to view a copy of the full job description please visit our website https://www.ebi.ac.uk/about/jobs - Reference Number: EBI01617
To apply please submit a covering letter and CV through our online system.
Applications are welcome from all nationalities and this will continue after Brexit. For more information please see our website. Visa information will be discussed in more depth with applicants selected for interview.
EMBL-EBI is committed to achieving gender balance and strongly encourages applications from women, who are currently under-represented at all levels.
This position is limited to the project duration specified.
Appointment will be based on merit alone.