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Bioinformatician (Anywhere)

Career description

At Lifebit, we carve our own path. So can you.

We’re open source pioneers, innovators changing the world. Our driving mission: to revolutionise bioinformatics and biomedical data analysis forever.

Our product, Lifebit CloudOS, is the world’s first federated genomics platform for unified, secure research over distributed big data. No one on the planet has anything close. Think best-in-class UI/UX, seamless integration with open-source tools, powerful cohort browser, advanced AI. We’re leading the industry and leaving competitors in the dust. We intend to keep it that way.

Because while we know our technology is unmatched, we also know we can keep making it greater. That’s why we need more superstars like you – to help take us to incredible new heights. (Plus, we’ve got some really big plans afoot…)

If you share our commitment to open source, bioinformatics, big big data, Machine Learning, and AI we want to hear from you today.

As a Bioinformatician in our team, you will:

  • Build required pipelines for batch analysis
  • Build and understand bioinformatics pipelines and monitoring
  • Provide upgrades, patches and maintenance of pipelines
  • Provide professional bioinformatics customer support assistance
  • Provide best practices support on building customer bioinformatics solutions
  • Engage with Lifebit clients and keep them excited about our products and services
  • Gather insights and experiences from every project and client to feed it to the rest of the team
  • Help and train team members and collaborators working with Lifebit products and services
  • Keep up to date with best practices and latest developments in bioinformatics data analysis areas

Requirements

We are looking for pioneering Bioinformaticians to join our team today. Please view these role requirements as just an indication of what we’re looking for – sometimes the perfect candidate is far more or less experienced than we anticipated. If you think that might be your case, please reach out and let us know!

You have demonstrable knowledge and experience in bioinformatics, specifically you have experience in:

  • 3+ years experience working with workflow management systems like Nextflow, CWL, Cromwell/WDL and Snakemake.
  • Or 5+ years experience working with Python and/or R.
  • 3+ years experience creating complex workflows/pipelines with many process to analysis large scale NGS data (ie. >10.000 genomes).
  • Or extensive experience in building Open Source Tools/Frameworks
  • Using workflow containers, including Docker and Singularity
  • Running workflow over HPC
  • Cloud systems (regardless of platform)
  • Data analysis on Python, Pandas or R
  • Creating interactive applications either through Python, R Shiny or similar frameworks

Additionally, we are looking for candidates who:

  • Have strong communication skills, both oral and written, with attention to detail
  • Can develop strong relationships with a range of stakeholders
  • Are able to organise and structure biomedical information, and be outcome oriented
  • Have experience with population genetics, genome-wide association studies

Benefits

What we offer in return:

  • £35k-75k salary dependent on experience, and generous stock options
  • 25 days of annual leave plus the usual public holidays
  • Mindfulness sessions and Mental Health tools
  • Monthly team activities
  • Conferences, events and training resources (Data science, AI, cloud, any tech stack, painting, origami, you pick!) – we offer £1,000 a year to each person for personal development)
  • International and diverse team
  • Exposure to problems and applications in the cloud, data analysis, ML, life sciences and big data fields
About "Lifebit"

Lifebit is democratising muti-omics, biomedicine & big data analysis with its AI-powered cloud-based system. This enables developers & researchers, no matter their computational & data analysis training level, & their corresponding organisations (ie. startups, SMEs, pharmaceutical companies), to instantly run & scale such analysis in a cost-speed-efficient and reproducible way that automates the analysis processes, learns from the data and provides actionable insights.

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Engineering
Remote
Competitive
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