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- Tasks: Lead innovative projects in computational biology and develop cutting-edge metabolic models.
- Company: Join the University of Liverpool and Syngenta's dynamic R&D hub.
- Benefits: Gain valuable experience in a collaborative environment with a focus on diversity.
- Why this job: Make a real impact on global food security through advanced research.
- Qualifications: PhD in Computational Biology or related field, with Python skills.
- Other info: Fixed-term role for 24 months with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
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 Jealotts Hill. This project aims to revolutionize 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. 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.
Our commitment to Equality, Diversity and Inclusion: 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 Liverpool employer: Borcheck & Gase, LLC
Contact Detail:
Borcheck & Gase, LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Biologist - Metabolic Modelling & Deep Learning in Liverpool
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biology and metabolic modelling. Attend relevant conferences or webinars, and don’t be shy to slide into DMs on LinkedIn. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and deep learning methods. This could be anything from GitHub repositories to blog posts explaining your work. We want to see your passion and expertise shine through!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to computational biology and metabolic modelling. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search. Don’t forget to tailor your application to highlight your experience with genome-scale metabolic modelling and deep learning!
We think you need these skills to ace Computational Biologist - Metabolic Modelling & Deep Learning in Liverpool
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 mention any relevant projects or publications that showcase your skills.
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 background aligns with the goals of the project. Be sure to mention your PhD and any specific techniques like AlphaFold2 that you’ve worked with.
Showcase Your Technical Skills: Since this role requires proficiency in Python and genome-scale metabolic modelling, make sure to highlight these skills prominently. If you have experience with multi-omics data processing, definitely include that too!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at Borcheck & Gase, LLC
✨Know Your Stuff
Make sure you brush up on your knowledge of genome-scale metabolic modelling and deep learning methods like AlphaFold2. Be ready to discuss how these techniques can be applied to crop protection and pathogen analysis, as this will show your genuine interest in the role.
✨Showcase Your Experience
Prepare to talk about your previous projects, especially those involving multi-omics data or computational pipelines. Highlight any high-impact scientific papers you've published, as this will demonstrate your ability to contribute to Syngenta's research goals.
✨Ask Smart Questions
Think of insightful questions to ask during the interview. Inquire about the specific challenges they face in developing their computational pipeline or how they envision integrating new methods into their existing frameworks. This shows you're engaged and thinking critically about the role.
✨Emphasise Diversity and Inclusion
Since the company values diversity, don't hesitate to share your unique perspective or experiences that align with their commitment to equality. This could set you apart and show that you resonate with their values.