Computational method development for finding novel drug targets by dissecting spatiotemporal events in myelofibrosis
Myeloproliferative neoplasms (MPN) are cancers that arise in the bone marrow. Key issues about the formation, progression and expansion of mutated clones, especially the spatial distribution of malignant clones and their interaction with stromal cells need to be further explored to identify novel precision drug targets and develop patient stratification biomarkers. We are looking for a highly motivated and team-oriented PhD student with expertise in machine learning, and single-cell transcriptomics to join our Translational Data Science lab.
• Masters or equivalent in a quantitative discipline such as bioinformatics, computer science, data science, machine learning
• Demonstrated good knowledge of programming in Python/ R
• Experience with sc/ snRNA-seq data analyses is essential
• Hands-on experience with predictive analyses using machine learning is preferred
• Previous experience with implementing deep learning tools for biomedical data analyses is desirable
• Fluent English skills
• Excellent teamwork skills
Please contact via email. We are at ISMB/ECCB in Lyon, so feel free to meet in-person-