biology data scientist i

il y a 2 semaines


Paris, Île-de-France STATION F Temps plein

AboutAt WhiteLab Genomics, we believe that every patient deserves access to life-saving treatments. We won't rest until that belief becomes a reality.Driven by our commitment to transforming the future of healthcare, we've earned our place among the top innovators, includingY Combinator, French Tech 2030,andFuture 40 by Station F. We've also been recognized byThe Galien Foundationas a"Best Startup"in healthcare innovation and asManufacturing Tech Disruptor of the Year - 2024atAdvanced Therapy Awards: Phacilitatein the USA, among other accolades.We're committed to revolutionizing genomic medicine, delivering single-dose cures to millions with cancer and neurodegenerative and rare diseases worldwide.By integrating cutting-edge data science, computational biology, and structural biology to design genomic medicine vectors with unprecedented precision, we're advancing the frontiers of healthcare and addressing critical challenges with the highest stakes.If you're passionate about improving patient outcomes and the intersection of biology and technology, we'd love to meet youJoin us– together, we'll bring life-saving treatments to the people who need them most.Job DescriptionComputational Biology team plays a key role in the analysis of multi-omic datasets, with a focus on single-cell RNA and DNA analysis, to support our research efforts to improve drug design in gene and cell therapy. Moreover, the computational biologist actively participates in the development of WLG's In-silico tools, pipelines and models, notably for payload design and manufacturing process optimization. The Data Scientist will work under close supervision, receiving clear instructions and guidance from senior scientists, the Principal Scientist and the Head of Computational Biology.OurComputational Biology Teamplays a key role in the development of predicting and optimization tools for payload design and manufacturing in the context of gene and cell therapy. We perform analysis of multi-omic datasets, with a focus on single-cell RNA and DNA data, to support our research efforts to improve drug design in gene and cell therapy. Moreover, the computational biologist actively participates in the development of WLG's In-silico tools, pipelines and models.We are looking for highly skilled and collaborative individuals who are naturally curious, have a passion for learning and solving complex problems with a "can-do" mindset.As aData Scientist, here's how you will make an impact: You willDesign and run new models for Whitelab Genomics' projects, with a particular focus on bioprocess optimization.Contribute to the development of new Machine Learning models implementations, features and applications of WhiteLab Genomics' gene and cell therapy platform.Help in the development and knowledge of extraction from several databases.Support the development of biological data analysis pipelines.Collaborate closely with cross-functional teams.Preferred ExperienceWe're eager to meet you if you haveRecent PhD or master's in data science, computational biology, bioinformatics, biostatistics, or a related field1–4 years of experience in Data Science and ML/DL in bioinformatics, biotech or biomedical contextProficient use of Python and bash and the standard machine learning libraries (scikit-learn, TensorFlow, PyTorch, etc...)Excellent communication skills, with the ability to effectively convey complex concepts to a non-technical audienceNice to haveExperience/knowledge in bioprocess optimizationExperience with generative models (GANs, diffusion, etc…)Experience in omics data analysisExperience/knowledge in gene and cell therapyExperience in client-facing rolesDocker, deployment pipelines, and software development skillsRecruitment ProcessTeams with Sara & Dina Z (comp-bio team)Teams with Dina L (People & Culture team)Interview in person (comp-bio team + P&C)Additional InformationContract Type: Full-TimeLocation: ParisEducation Level: PhD and moreExperience: > 2 yearsPossible partial remote


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