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Data Scientist/Senior Data Scientist - P Znamenskiy lab Reporting to: Petr Znamenskiy, Group Leader (The Francis Crick Institute) Contact term: This is a full-time, fixed term (3-year) position
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information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some
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, plant transformation, plant breeding, computer vision assisted automated phenotyping, machine learning and AI. The role will require working with other institutional stakeholders to scope, design, equip
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research and unite our researchers around our Technology Innovation Challenges and Life Science Challenges. For more information on the Franklin’s Challenges click here . As a Research Associate in Chemical
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. The successful candidate will assist with data collection, maintain accurate records, and uphold rigorous laboratory safety and maintenance standards. With responsibilities spanning inventory management, equipment
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computational methods and algorithms for genomic sequencing data analysis, particularly in the context of genome assembly. This is an exciting opportunity to develop novel computational approaches for microbial
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central to shaping a newly established and rapidly scaling Plant Biology Institute with the ambition to become a global leader in plant phenotyping and data-driven plant science. The successful candidate
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of emerging methods in metabolic analysis, metabolic modelling, machine learning, and data-driven biology, identifying opportunities to apply new tools to accelerate discovery. Work closely with experimental
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candidate will: Demonstrate experience in biological and clinical data analysis and across a range of NGS applications. Demonstrate experience in generative AI tools and advanced bioinformatics pipelines
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the intellectual energy and independent thinking necessary to lead a programme of cutting-edge research and to shape the overall aims and success of the group. Drive rigorous experimental design, execution, and data