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: Collaborative environment with dynamic projects and career advancement opportunities.
- Why this job: Make a real impact in molecular design at the forefront of science and technology.
- 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: Expedeon Inc. (an Abcam company)
Abcam is an exceptional employer located in the vibrant city of Cambridge, UK, offering a dynamic work culture that fosters innovation and collaboration at the intersection of structural biology and AI. Employees benefit from cutting-edge projects, opportunities for professional growth, and a supportive environment that encourages creativity and interdisciplinary teamwork, making it an ideal place for those passionate about advancing molecular design through technology.
Contact Details:
Expedeon Inc. (an Abcam company) Recruitment Team
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 relevant meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to protein design and machine learning. Whether it’s GitHub repos or case studies, having tangible evidence of your expertise can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you’ll likely need to communicate with both technical and non-technical stakeholders. We recommend mock interviews to get comfortable!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you a leg up in the hiring process. So, what are you waiting for? Get your application in!
We think you need these skills to ace Senior Computational Protein Design & AI Scientist in Cambridge
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your expertise in AI/ML for molecular design. We want to see how your experience with protein structural modelling and generative design can shine through in your application.
Tailor Your Application:Don’t just send a generic CV! We love it when applicants tailor their applications to the role. Mention specific projects or experiences that relate directly to computational design of miniproteins, VHHs, and antibodies.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that communicate your ideas effectively without unnecessary fluff.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Expedeon Inc. (an Abcam company)
✨Know Your Stuff
Make sure you brush up on your knowledge of computational design, especially around miniproteins, VHHs, and antibodies. Familiarise yourself with the latest machine learning approaches, particularly LLMs and diffusion-based models, as these will likely come up in conversation.
✨Showcase Your Experience
Prepare to discuss your past projects in computational biology or AI for molecular design. Be ready to share specific examples where you've successfully navigated complex scientific data problems, and how your expertise has contributed to successful outcomes.
✨Collaboration is Key
Since this role involves working closely with wet-lab teams, think about how you can demonstrate your collaborative skills. Have examples ready that showcase your ability to work in multidisciplinary settings and how you’ve driven iterative design cycles in the past.
✨Communicate Clearly
You’ll need to communicate results to both internal and external stakeholders, so practice explaining complex concepts in a straightforward way. Think about how you can convey your findings effectively, using visuals or analogies if necessary to make your points clear.
