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You will focus on analysing single cell long read RNAseq data generated by our team. You will work to discover cell specific isoforms and relate them to pathological signatures and genetic risk factors in ALS patient tissue. You will apply supervised and unsupervised machine learning methods using a local high performance computing cluster. You will work closely with experts in ALS, bioinformatics, neuroscience and RNA biology. You will support in the supervision of more junior researchers and students.
You will work in the department of translational neuroscience at the UMC Utrecht. You will also function as a member of the Dutch ALS research center and the Utrecht Bioinformatics Center.
You have a PhD in bioinformatics, genomics or neuroscience with at least 1 first author publication. You are ambitious, have strong communication skills and are a good presenter / scientific writer. You enjoy being proactive and taking a leading role in your work. You can envisage providing mentorship to junior researchers / students. You can work both independently and as part of a team when needed. You have experience in advanced bioinformatic analyses of omics datasets, preferably single cell and/or long read RNAseq data.
Demonstrable experience in advanced machine learning and/or high performance computing is an advantage. Prior lab experience in genomics / tissue analyses is an advantage but not required(eg NGS library preparations, tissue sectioning, qPCR, smFISH).
For further details, please contact the project supervisor Dr Kevin Kenna ([email protected])

Wij geloven in de kracht van een divers team waarin ruimte is voor verschillende vaardigheden, expertises, sociale en culturele achtergronden. Wij zijn benieuwd naar jou!
Onze nieuwe collega's werven we zelf. We hebben geen behoefte aan acquisitie.
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