Plant Genomics and Machine Learning Scientist
Plant Genomics and Machine Learning Scientist

Plant Genomics and Machine Learning Scientist

Abingdon Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us to enhance crops using genomics and machine learning for sustainable farming.
  • Company: Wild Bio is an innovative Oxford University spin-out focused on sustainable agriculture.
  • Benefits: Enjoy flexible working, private medical insurance, and regular team socials.
  • Why this job: Make a real impact on global food security while working with cutting-edge science.
  • Qualifications: Ph.D. in bioinformatics or related field; expertise in machine learning and plant science required.
  • Other info: On-site work at least three days a week is necessary for team collaboration.

The predicted salary is between 36000 - 60000 £ per year.

Job Description

Who we are:

At Wild Bio we are radically enhancing crops to feed the world sustainably and promote a wilder planet. Wild plants have had half a billion years to evolve natural solutions for thriving in almost every environment on Earth. Our proprietary genetics platform harnesses these wild innovations to enhance the world’s most important crops. Wild-enhanced crops would simultaneously boost farm yields and promote gigaton-scale carbon mitigation strategies. If you’re looking for a start-up that has enormous potential for impact on growers, consumers, and the planet, please read on.

Wild Bio is a well-funded, fast-paced Oxford University spin-out working from state-of-the-art labs and offices at Milton Park, Oxfordshire. We are about to enter an exciting phase of growth and are looking for an experienced, driven, and curious Plant Genomics and Machine Learning Scientist to join us and significantly contribute to delivering the change we believe in.

The role:

We’re looking for someone who is excited to work at the intersection of evolutionary biology, machine learning, and plant physiology. The ideal candidate will have previous experience in some combination of comparative genomics, bioinformatics, machine learning, and plant science. Their task will be to help create, curate, and mine deep genomics and plant physiology datasets for insights into creating the world’s highest performing crops.

Detailed responsibilities:

  • Build novel comparative genomics pipelines to identify targets for improving crop performance.
  • Mine and curate public datasets for useful additions to our machine learning (ML) datasets.
  • Collaborate closely with the experimental biology team to guide the generation of new datasets to be integrated into our ML pipelines.
  • Leverage your understanding of plant physiology to generate unique insights into plant performance, ensuring a steady stream of ML predictions are prioritised and ready for empirical validation.
  • Stay up to date with the latest advancements in the field – e.g. by attending relevant conferences, scouting for new tools and methods, and ensuring a continuous improvement mindset within the computational team.
  • Help guide the evolution of the computational infrastructure, including hardware and software resourcing decisions.
  • Effectively communicate results, problems, and deliverables to a diverse array of stakeholders
  • Provide bioinformatics expertise to those around you as needed, adopting a coaching and mentoring approach where appropriate.

Knowledge and skills:

  • An advanced degree (e.g. Ph.D.) in bioinformatics, computational biology, genomics, or a related field where bioinformatics and statistics are applied to large biological datasets.
  • Expertise in some combination of comparative genomics, molecular evolution, machine learning, evolutionary biology, and/or plant science.
  • Proficiency with machine learning packages in Python and/or R (e.g., Scikit-learn, TensorFlow, PyTorch, Caret).
  • Fluency in Python or R, and comfortable working in Linux/Unix.
  • Experience working with git and Github.
  • Experience working in plant science, or with data from non-model species.
  • Excellent communication skills and the ability to work effectively in a multidisciplinary team that includes wet lab scientists.
  • Strong problem–solving skills, with an ability to think creatively to meet goals and deadlines.
  • Keen to seek out new opportunities to develop, share learnings with others, and strive to support others in their own development and growth.
  • Have a curious and courageous mindset, enjoy stepping up to try new things in a changing environment, and taking initiative where there is often ambiguity.
  • Challenge established approaches with the aim of improving the system.
  • Take initiative where needed with tasks that have not been assigned.

Benefits:

  • Group life cover x 3 of base salary.
  • Pension.
  • Private medical insurance.
  • Enhanced maternity and paternity pay.
  • Regular company socials.
  • Complimentary refreshments throughout the week.
  • Team meals including breakfast on a Monday and lunch each Friday, creating opportunities for informal networking and team bonding.
  • Training and development opportunities.
  • Flexible working opportunities.
  • Opportunity to work with cutting edge science.

Location

We’re headquartered in Milton Park, a business and technology park in Oxfordshire. While we do offer flexible and hybrid working, we are also a small, fast-paced team working on cutting-edge science, and we believe the relationships forged and the work we do in-person will be crucial for our success. For this reason, we are asking that applicants be able to work on-site at least three days a week.

The successful candidate will be required to provide proof of eligibility to work in the UK or indicate if sponsorship is required.

Plant Genomics and Machine Learning Scientist employer: Wild Bioscience

At Wild Bio, we are not just a start-up; we are a mission-driven team dedicated to revolutionizing agriculture through innovative plant genomics and machine learning. Located in the vibrant Milton Park, Oxfordshire, we offer a dynamic work environment that fosters collaboration and creativity, alongside competitive benefits such as private medical insurance, enhanced parental leave, and regular team socials. Join us to be part of a passionate team where your contributions will directly impact sustainable farming practices and the health of our planet.
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Contact Detail:

Wild Bioscience Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Plant Genomics and Machine Learning Scientist

✨Tip Number 1

Familiarize yourself with the latest advancements in plant genomics and machine learning. Attend relevant conferences or webinars to network with professionals in the field and gain insights that can set you apart during interviews.

✨Tip Number 2

Showcase your experience with comparative genomics and bioinformatics by discussing specific projects you've worked on. Be prepared to explain how your contributions led to improved crop performance or innovative solutions.

✨Tip Number 3

Highlight your proficiency in Python or R, especially with machine learning packages. Consider preparing a small portfolio of code samples or projects that demonstrate your skills in these areas to share during the interview process.

✨Tip Number 4

Emphasize your ability to work collaboratively in multidisciplinary teams. Prepare examples of how you've effectively communicated complex scientific concepts to non-experts, as this will be crucial in a role that involves diverse stakeholders.

We think you need these skills to ace Plant Genomics and Machine Learning Scientist

Comparative Genomics
Bioinformatics
Machine Learning
Plant Science
Data Mining
Python Programming
R Programming
Linux/Unix Proficiency
Git and GitHub Experience
Statistical Analysis
Communication Skills
Problem-Solving Skills
Collaboration in Multidisciplinary Teams
Curiosity and Initiative
Continuous Improvement Mindset

Some tips for your application 🫡

Understand the Company Mission: Before applying, take some time to understand Wild Bio's mission and values. Highlight how your background in plant genomics and machine learning aligns with their goal of enhancing crops sustainably.

Tailor Your CV: Make sure your CV reflects your experience in comparative genomics, bioinformatics, and machine learning. Use specific examples that demonstrate your skills and achievements relevant to the role.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for plant science and machine learning. Discuss how your unique insights and experiences can contribute to Wild Bio's innovative projects.

Showcase Relevant Projects: If you have worked on projects involving machine learning in plant science or bioinformatics, be sure to mention them. Include any publications or presentations that highlight your expertise in these areas.

How to prepare for a job interview at Wild Bioscience

✨Show Your Passion for Plant Science

Make sure to express your enthusiasm for plant genomics and machine learning during the interview. Share specific examples of projects or research that ignited your interest in these fields, as this will demonstrate your genuine commitment to the role.

✨Highlight Relevant Experience

Prepare to discuss your previous experience in comparative genomics, bioinformatics, and machine learning. Be ready to provide concrete examples of how you've applied these skills in past roles, especially in relation to improving crop performance or working with large biological datasets.

✨Demonstrate Collaboration Skills

Since the role involves close collaboration with experimental biology teams, be prepared to talk about your experience working in multidisciplinary teams. Highlight instances where you effectively communicated complex ideas to non-experts and contributed to team success.

✨Stay Updated on Industry Trends

Show that you are proactive about staying informed on the latest advancements in plant science and machine learning. Mention any relevant conferences you've attended or new tools you've explored, as this reflects your commitment to continuous improvement and innovation in the field.

Plant Genomics and Machine Learning Scientist
Wild Bioscience
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  • Plant Genomics and Machine Learning Scientist

    Abingdon
    Full-Time
    36000 - 60000 £ / year (est.)

    Application deadline: 2027-03-14

  • W

    Wild Bioscience

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