SonicJobs Logo
Login
Left arrow iconBack to search

Bioinformatician, non-model species, NGS pipelines, Python, Machine Learning, COR7292

Corriculo Ltd
Posted 22 days ago, valid for a month
Location

Oxford, Oxfordshire OX4 2WA, England

Contract type

Full Time

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

SonicJobs' Terms & Conditions and Privacy Policy also apply.

Sonic Summary

info
  • My client, a cutting-edge start-up within the AgriTech space, is seeking a Bioinformatician with a PhD in Bioinformatics, Genomics, or a related field, and at least 3 years of relevant experience.
  • The position involves designing and developing NGS pipelines for the analysis of non-model species, specifically in the context of plant science.
  • Candidates should have experience with de novo transcriptome assembly, machine learning, and proficiency in Python and libraries such as SciPy and Pandas.
  • This role offers a competitive salary, share options, private medical benefits, and excellent opportunities for career development.
  • The company, an Oxford University spin-out, focuses on innovative genetic technologies to enhance agriculture and promote climate resilience.

Bioinformatician, non-model species, NGS pipelines, Python, Machine Learning, COR7292

My client, a cutting-edge start-up within the AgriTech space, is seeking a Bioinformatician with experience in designing and developing NGS pipelines for the analysis of non-model species to join their growing R&D team. This is an exceptional opportunity to work on breakthrough innovations that aim to transform global agriculture through data-driven insight.As the Bioinformatician you’ll play a critical role in building and optimising next-generation sequencing (NGS) pipelines for diverse, non-model plant species. You'll curate and mine large datasets to identify key traits that can drive the development of high-performing, climate-resilient crops. You’ll also have the opportunity to apply cutting-edge tools such as machine learning and AI and work collaboratively with experimental biologists to turn genomic insights into real-world agricultural impact.The CompanyThis dynamic and well-funded Oxford University spin-out is developing pioneering genetic technologies that tap into nature’s wild innovations to strengthen the world’s key crops. With significant backing and an ambitious roadmap, this team is set to make a global impact on farming, food security, and climate resilience.Benefits

  • Share options
  • Private Medical
  • Excellent opportunities for career development
  • Sponsorship available

What’s required of the Plant Scientist?

  • A PhD in Bioinformaticians, Genomics, Plant Science, or a related field, with relevant academic or industry experience
  • Experience designing and developing NGS pipelines for the analysis of non-model species, if this has been within plants even better
  • Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data
  • Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc.

What Next?If you’d like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I’d love to chat! If you’re ready to apply, please submit your CV today.

Bioinformatician, non-model species, NGS pipelines, Python, Machine LearningCorriculo Ltd acts as an employment agency and an employment business. #INDSCI, #ChannelC, #MR

Apply now in a few quick clicks

In order to submit this application, a Reed account will be created for you. As such, in addition to applying for this job, you will be signed up to all Reed’s services as part of the process. By submitting this application, you agree to Reed’s Terms and Conditions and acknowledge that your personal data will be transferred to Reed and processed by them in accordance with their Privacy Policy.

SonicJobs' Terms & Conditions and Privacy Policy also apply.