At a Glance
- Tasks: Lead cutting-edge computational design for proteins using AI and machine learning.
- Company: Join Abcam, a leader in innovative biotechnological solutions.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic, multidisciplinary environment with excellent career advancement opportunities.
- Why this job: Make a real impact in molecular design at the intersection of biology and AI.
- Qualifications: 5+ years in computational biology or AI, with strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
You will evaluate, develop and utilize cutting‑edge computational design for miniproteins, VHHs (nanobodies), and antibodies, leveraging modern machine learning approaches including large language models (LLMs) and diffusion‑based generative models. This role sits at the interface of structural biology, computational modeling, and AI‑driven molecule design. This position reports to the Director of Data Applications and Analytics at Abcam and will undertake projects for the Danaher Affinity Reagents Autonomous Laboratory and is based in Cambridge, UK.
In This Role, You Will Have The Opportunity To:
- Lead computational design of miniproteins, VHHs, and antibodies.
- Apply and integrate LLM‑based and diffusion‑based generative models with structure‑ and physics‑based protein design methods.
- Collaborate closely with wet‑lab, to drive iterative design/make/test/learn cycles.
- Analyze structural, biophysical, and binding data to refine models and improve design quality.
- Contribute to strategy and communicate results to internal and external stakeholders.
The Essential Requirements Of The Job Include:
- Expertise in AI/ML for molecular design, such as protein structural modelling, generative protein or antibody design, optimization of binding, developability, or stability profiles.
- Familiarity with immune repertoire sequencing, phage/yeast display, or experimental modalities used to assess and optimize biomolecule properties.
- Strong grounding in statistics, applied mathematics, and computational modelling.
- Fluency in Python, including rapid prototyping, production‑quality code, and use of relevant bioinformatics and ML libraries.
- Ability to navigate and solve complex, ambiguous scientific data problems with creativity and rigor.
- 5+ years of relevant experience in computational biology, bioinformatics, or AI for molecular design.
It would be a plus if you also possess previous experience in:
- Software engineering best practices and collaboration with engineering teams.
- MLOps or model lifecycle management.
- Working with databases, data integration strategies, and data modelling.
- Working in dynamic, multidisciplinary settings.
- Learning new tools and applying them to complex biological challenges.
Senior Computational Protein Design & AI Scientist in Cambridge employer: Abcam
Abcam is an exceptional employer, offering a dynamic work environment in the heart of Cambridge, UK, where innovation thrives at the intersection of structural biology and AI. Employees benefit from a collaborative culture that encourages professional growth through cutting-edge projects and access to advanced technologies, while also enjoying a strong commitment to work-life balance and employee well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Computational Protein Design & AI Scientist in Cambridge
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biology and AI. Attend meetups, webinars, or conferences where you can connect with potential employers and showcase your passion for miniproteins and antibody design.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects involving AI/ML in molecular design. Include any relevant code snippets or case studies that demonstrate your expertise in Python and computational modelling.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of structural biology and generative models. Be ready to discuss how you've tackled complex scientific data problems and how you can contribute to the team at Abcam.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Computational Protein Design & AI Scientist in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in AI/ML for molecular design and computational biology. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about this role at StudySmarter and how your background makes you a perfect fit. We love seeing genuine enthusiasm and a clear connection to our mission.
Showcase Your Technical Skills:Don’t forget to mention your fluency in Python and any experience with bioinformatics or ML libraries. We’re keen on candidates who can navigate complex data problems, so give us examples of how you’ve tackled challenges in the past.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re proactive and ready to join our team!
How to prepare for a job interview at Abcam
✨Know Your Stuff
Make sure you brush up on your knowledge of computational design, especially around miniproteins and VHHs. Familiarise yourself with the latest machine learning approaches, particularly LLMs and diffusion-based models, as these will likely come up in conversation.
✨Show Your Collaborative Spirit
Since this role involves working closely with wet-lab teams, be ready to discuss your experience in collaborative projects. Share specific examples where you’ve successfully driven iterative design cycles and how you communicated results to stakeholders.
✨Demonstrate Problem-Solving Skills
Prepare to showcase your ability to tackle complex scientific data problems. Think of instances where you navigated ambiguity and used creativity to find solutions. This will highlight your analytical skills and adaptability.
✨Get Technical with Python
Fluency in Python is a must for this role. Be prepared to discuss your experience with rapid prototyping and production-quality code. If possible, bring examples of relevant bioinformatics or ML libraries you've worked with to demonstrate your technical prowess.
