Responsibilities;
*Working collaboratively with the computational biology team and experimental stem cell scientists to support their ambitious research programmes
*Implementation of novel workflows to efficiently mine information from complex biological data sets
*Development and application of novel machine learning approaches to help guide cellular reprogramming efforts
*Using genomic perturbation data to produce models of cellular differentiation.
Requirements:
*PhD/MSc in computational biology, computer science, or a related discipline with a strong statistical, data science or machine learning component.
*Experience or industry equivalent in data science/machine learning, ideally in the genomics space.
*Experience with machine learning libraries, such as Scikit-learn, TensorFlow, PyTorch, Keras, etc.
*Strong programming skills in python.
*Experience with managing and analysing large volumes of genomic data and result
*Good knowledge of bioinformatics tools, resources and public databases
*Enjoy tackling research challenges through critical thinking, scientific rigour and inventiveness
Ideally;
*Experience of applying machine learning methods to scRNA-seq data
*Familiarity with gene regulatory networks, mechanisms of gene expression, developmental biology, and stem cell biology.
*Experience with cloud computing (preferably AWS) and workflow management tools or batch scheduling systems
*Familiarity with version control systems for code reproducibility
*Strong programming skills in R
