At a Glance
- Tasks: Design and optimise bioinformatics pipelines to tackle real-world challenges.
- Company: Join the innovative Ellison Institute of Technology, where science meets impact.
- Benefits: Enjoy enhanced holiday pay, private medical insurance, and a supportive work environment.
- Why this job: Make a difference in health, AI, and sustainability while collaborating with visionary experts.
- Qualifications: PhD or equivalent experience in bioinformatics and proven success in real-world applications.
- Other info: Be part of a dynamic team that values creativity, collaboration, and personal growth.
The predicted salary is between 30000 - 50000 £ per year.
At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges in four transformative areas: Health, Medical Science & Generative Biology, Food Security & Sustainable Agriculture, Climate Change & Managing CO₂, Artificial Intelligence & Robotics. This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas for lab to society.
Requirements
We are looking for a Bioinformatician who will apply their strong expertise in bioinformatics and software engineering to advance EIT's programmes. You will collaborate with Applied and Research Scientists, Engineers, subject matter experts, users, and leadership to build AI solutions in our endeavour to respond to humanity’s most challenging problems.
Day-to-Day, you might:
- Design, implement, and optimize state-of-the-art bioinformatics pipelines.
- Transform and enrich large-scale biological data for training AI models including assembly, quality control, phylogeny and annotations.
- Design biologically relevant tasks for training ML models and build corresponding evaluation data sets and metrics.
- Design protocols for experimental model validation in collaboration with internal and external partners.
- Collaborate effectively within a multi-disciplinary team and work closely with subject matter experts to incorporate domain expertise and user needs.
- Build robust, scalable, and re-usable pipelines, maintaining high standard of code quality and transparency.
- Communicate the design, function, performance, and output of bioinformatics pipelines to internal and external stakeholders.
What Makes you a Great Fit:
- PhD or equivalent experience in Bioinformatics, Computational Biology, Microbiology, Genetic Epidemiology, Genomics or a related discipline.
- Extensive experience as a Bioinformatician including proven success in implementing state-of-the-art approaches on real-world problems, e.g., genome assembly, alignment, phylogeny and molecular evolution, genome annotation, and gene enrichment analysis.
- Hands-on experience analysing genomics, (spatial-)transcriptomics, proteomics data.
- Experience working with large datasets and building robust, scalable pipelines to transform them.
- Hands-on experience building Machine learning models using bioinformatics approaches (e.g., kmers) and keen interest in Machine Learning.
- Proficiency in Python and experience adhering to best-practice coding practices.
- Experience with containerization, relevant workflow management tools and parameter management.
- Excellent communication skills including the ability to convey technical concepts to audiences of a variety of backgrounds.
It would be Great to also have:
- Proven ability to work in fast-paced, dynamic environments like start-ups (e.g., willingness to take up multiple roles, high degree of autonomy).
- Experience in Machine Learning and tackling challenges in biological and molecular discovery.
- Experience with Kubernetes and cloud platforms or HPC environments (e.g., Slurm).
- Familiarity with both long- and short-read technologies (e.g. ONT, Illumina).
Benefits
- Enhanced holiday pay.
- Pension.
- Life Assurance.
- Income Protection.
- Private Medical Insurance.
- Hospital Cash Plan.
- Therapy Services.
- Perk Box.
- Electric Car Scheme.
Why work for EIT:
At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!
Bioinformatician in Oxford employer: Ellison Institute of Technology
Contact Detail:
Ellison Institute of Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Bioinformatician in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the bioinformatics field, especially those connected to EIT. Attend relevant events or webinars and don’t be shy about introducing yourself. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your bioinformatics projects, especially any AI solutions you've developed. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex bioinformatics concepts in simple terms. Remember, at EIT, they value collaboration and clear communication, so show them you can connect with diverse teams!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of the EIT community and making a real-world impact.
We think you need these skills to ace Bioinformatician in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Bioinformatician role. Highlight your expertise in bioinformatics, software engineering, and any relevant projects you've worked on that showcase your ability to tackle real-world problems.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about the work we do at EIT. Share specific examples of how your background and skills can contribute to our mission of translating scientific discovery into real-world impact.
Showcase Your Communication Skills: Since you'll be collaborating with a multi-disciplinary team, it's important to demonstrate your ability to communicate complex technical concepts clearly. Include examples in your application where you've successfully conveyed information to diverse audiences.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Ellison Institute of Technology
✨Know Your Bioinformatics Inside Out
Make sure you brush up on your bioinformatics knowledge, especially the latest techniques in genome assembly and machine learning applications. Be ready to discuss specific projects you've worked on and how they relate to the role at EIT.
✨Showcase Your Collaboration Skills
EIT values teamwork, so prepare examples of how you've successfully collaborated with multi-disciplinary teams. Highlight your ability to communicate complex concepts clearly to both technical and non-technical stakeholders.
✨Demonstrate Your Coding Proficiency
Since proficiency in Python is crucial, be prepared to discuss your coding practices and any relevant projects. You might even want to bring along a code sample that showcases your best work and adherence to best practices.
✨Be Ready for Problem-Solving Scenarios
Expect to tackle real-world problems during the interview. Think about challenges you've faced in previous roles and how you approached them, particularly in building scalable pipelines or working with large datasets.