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- Tasks: Develop cutting-edge computational pipelines for protein function prediction and metabolic modelling.
- Company: Join Syngenta, the world's largest agrochemical company, in a dynamic research environment.
- Benefits: Gain experience with high-performance computing and proprietary datasets while contributing to global food security.
- Why this job: Make a real impact on crop protection and food sustainability through innovative research.
- Qualifications: PhD in Computational Biology or related field, with Python proficiency and metabolic modelling skills.
- Other info: Collaborate with experts and publish high-impact scientific papers in a supportive, diverse team.
The predicted salary is between 36000 - 60000 £ per year.
The role involves developing a species-agnostic computational pipeline that integrates cutting-edge deep learning methods – such as AlphaFold2 and FoldSeek – to enhance protein function prediction and estimate kinetic parameters for enzyme-constrained models. By processing proprietary multi-omics data, you will initially focus on determining metabolic vulnerabilities in Zymoseptoria tritici before expanding the methodology to other species to support global food security.
Candidates should have a PhD in Computational Biology, Bioinformatics, or a related quantitative field, with proficiency in Python and a strong foundation in genome-scale metabolic modelling. This fixed-term post is available for 24 months.
The University of Liverpool and Syngenta Limited have established a Knowledge Transfer Partnership (KTP) to recruit a specialized Computational Biologist to join Syngenta's global R&D hub in Jealott's Hill. This project aims to revolutionise crop protection discovery by implementing a "biology-first" approach to pathogen analysis, focusing on the development of novel methods for constructing genome-scale metabolic maps of commercially relevant pathogens. You will lead the preparation and publication of high-impact scientific papers while embedding these workflows into Syngenta's target identification framework.
You will join the Bioscience Digital Group within the world's largest agrochemical company. You will work alongside data scientists and bioinformaticians, utilising Syngenta's high-performance computing infrastructure and rich proprietary datasets. You will be supervised industrially by Dr. Chris O'Grady, a Senior Principal Scientist in Computational Biology.
We are committed to enhancing a workforce as diverse as our community and particularly encourage applicants who are of minoritised genders and ethnic backgrounds, living with a disability, and/or are members of the LGBTQIA+ community.
Computational Biologist – Metabolic Modelling & Deep Learning in Bracknell employer: The Knowledge Transfer Network Limited
Contact Detail:
The Knowledge Transfer Network Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Biologist – Metabolic Modelling & Deep Learning in Bracknell
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biology on platforms like LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and metabolic modelling. This will give you an edge during interviews and help demonstrate your expertise in a tangible way.
✨Tip Number 3
Prepare for technical interviews by brushing up on deep learning methods and metabolic modelling concepts. Practice explaining your thought process clearly, as this will help you stand out when discussing complex topics with potential employers.
✨Tip Number 4
Don’t forget to apply through our website! We often have exclusive listings that might not be found elsewhere. Plus, it shows your genuine interest in joining our team at Syngenta and being part of something big in the agrochemical industry.
We think you need these skills to ace Computational Biologist – Metabolic Modelling & Deep Learning in Bracknell
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Computational Biologist. Highlight your experience with metabolic modelling and deep learning, and don’t forget to showcase your Python skills. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your expertise can contribute to our mission at Syngenta. Keep it engaging and relevant to the job description.
Showcase Your Research Experience: Since you'll be leading high-impact scientific papers, make sure to highlight any relevant research experience. Discuss your previous projects, especially those involving genome-scale metabolic modelling or multi-omics data, to show us what you can bring to the table.
Apply Through Our Website: We encourage you to apply through our website for a smooth application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Don’t miss out on this opportunity!
How to prepare for a job interview at The Knowledge Transfer Network Limited
✨Know Your Stuff
Make sure you brush up on your knowledge of metabolic modelling and deep learning techniques. Familiarise yourself with tools like AlphaFold2 and FoldSeek, as well as the specifics of genome-scale metabolic modelling. Being able to discuss these topics confidently will show that you're not just a candidate, but a passionate expert.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving multi-omics data or computational pipelines. Highlight your role in these projects and the impact they had. This is your chance to demonstrate how your experience aligns with the goals of the role at Syngenta.
✨Ask Insightful Questions
Come prepared with questions that show your interest in the company and the role. Inquire about the specific challenges they face in crop protection discovery or how they envision the integration of new methodologies into their existing frameworks. This not only shows your enthusiasm but also your critical thinking skills.
✨Emphasise Collaboration
Since you'll be working alongside data scientists and bioinformaticians, highlight your teamwork skills. Share examples of how you've successfully collaborated in the past, particularly in interdisciplinary settings. This will reassure them that you can thrive in their collaborative environment.