Sr. Scientist, Computational Biology
Cambridge, England
Applications have closed
Flagship Pioneering, Inc.
We are Flagship Pioneering We are a biotechnology company that invents platforms and builds companies that change the world. Latest News Companies…What if… you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies to transform human health and sustainability?
Company Summary:
FL86, Inc. is a privately held, early-stage company developing a novel genomics platform and therapeutics for diseases with a large unmet need.
FL86 was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA) Generate Biomedicines, Sana Biotechnology (SANA), Tessera Therapeutics, Evelo Biosciences (EVLO), Indigo Agriculture, Seres Therapeutics (MCRB), Syros Pharmaceuticals (SYRS), and Rubius Therapeutics (RUBY). To date, Flagship has deployed over $2.5 billion in capital toward the founding and growth of its pioneering companies alongside more than $19 billion of follow-on investments from other institutions. In 2021, Flagship Pioneering was ranked 12th globally on Fortune’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies.
Position Summary:
We are seeking a computational scientist (leveling flexible based on experience) who wants to leverage genomics data to identify new ways to treat human diseases. The candidate brings enthusiasm, intellectual curiosity, scientific rigor, and a deep-rooted desire to innovate in genomics. This role is based in the vicinity of Cambridge UK and hybrid work arrangements will be considered, but all applicants will require permission to work in UK.
Key Responsibilities:
- Be an active member of a scientific team focused on the design and deployment of bioinformatics, with the end goal of developing new therapeutics for diseases with large unmet needs
- Work on collaborative project teams to design experiments and analyze results to address underlying genomics questions
- Identify and integrate relevant structured and unstructured functional and genomics datasets into FL86’s database
- Develop and deploy statistical models to assess database for novel discoveries
- Participate in ongoing work on method development and analysis
- Communicate key findings to stakeholders across the company, in written and presentation formats
- Collaborate closely with other members across the organization
Requirements:
- PhD, or equivalent work-experience, in cancer genetics, human genetics, statistical genetics, computational biology, bioinformatics, genomics or similar discipline is required
- 0-5+ years of industry/post-doc experience working with genomics data, with ability to process, analyze, and interpret genetic datasets
- Can write and interpret data analysis code
- Candidates with experience in (a) Target Discovery, (b) Writing and operating data pipelines, or (c) Human or Cancer Genomics analysis will be preferred
- Strong leadership, management, and collaboration skills
- Excellent verbal and written communication.
- Ability to work successfully in a matrix environment, prioritize and manage multiple tasks simultaneously, integrate cross-functional issues and balance competing priorities effectively.
- A high degree of energy, accuracy and attention to detail, and a passion for creating transformative medicines for patients with serious diseases
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Bioinformatics Biology Data analysis Data pipelines Engineering Industrial Pharma PhD Pipelines Ruby Statistics
Perks/benefits: Flex hours Startup environment
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