At a Glance
- Tasks: Lead cutting-edge protein design and engineering projects using AI-driven techniques.
- Company: Join GSK, a leader in innovative healthcare solutions.
- Benefits: Enjoy competitive salary, bonuses, healthcare, and hybrid work options.
- Other info: Dynamic team environment with opportunities for learning and growth.
- Why this job: Make a real impact in drug discovery and shape the future of protein engineering.
- Qualifications: PhD in relevant field with experience in protein design and collaboration.
The predicted salary is between 60000 - 80000 £ per year.
This role will lead the development and deployment of state‑of‑the‑art in‑silico protein engineering and design principles for generation of complex reagents to progress the discovery portfolio. You will work collaboratively with computational experts and protein expression teams to design, generate, and test engineered proteins and to aid discovery of novel medicines. You will work closely with discovery project teams, computational scientists, and external partners, contributing to both scientific innovation and project delivery. This position offers strong visibility, opportunities for learning, and the chance to help shape next‑generation protein engineering capabilities within GSK. It is an opportunity to play a key role in advancing molecular design and engineering capabilities within LMR, supporting complex targets and next‑generation modalities. The role contributes directly to critical portfolio delivery and emerging technology platforms, including AI/ML‑enabled design approaches.
Responsibilities:
- Carry out construct design and protein engineering for the generation of complex proteins and panels of diverse protein classes, including multi‑subunit, multidomain and membrane proteins.
- Develop and deploy in silico Molecular Biology and Protein Design tools.
- Develop and execute experimental workflows that connect Molecular Biology design with laboratory automation.
- Collaborate with computational design, structural biology, and analytical teams to translate insights into experimental construct and protein design strategies.
- Develop approaches for external and internal database searching, for protein reagents and constructs.
- Build external collaborations and evaluate emerging technologies or vendors to enhance protein engineering capabilities.
- Develop workflows that enable data use and re‑use, and which maintain a high standard of data integrity.
- Manage timelines, communicate results, and provide clear scientific recommendations to cross‑functional teams.
Basic Qualifications & Skills:
- PhD in Biochemistry, Protein Engineering, Molecular Biology, or a related discipline and significant industry experience.
- Proven track record of construct and molecule design for the generation of complex antigens and panels of proteins of different classes; to include multi‑subunit and multidomain and membrane proteins.
- Demonstrated skills in experimental cloning and expression techniques for a range of different protein classes including multi‑subunit and multidomain and membrane proteins.
- Practical experience with high‑throughput expression systems and the use of automation.
- Proven track record of use of construct design tools (e.g. Snapgene, Genius Prime, VectorBuilder or similar).
- Proficiency in programming, data analysis and visualization tools and proven track record of using these skills for project delivery (e.g. Python, R or similar).
- Data skills and experience in manipulation of large volumes of data, and tools to enable efficient data analysis and visualisation (e.g. Spotfire or similar).
- Proven track record of working in partnership with computational scientists and working collaboratively across multidisciplinary teams.
- Evidence of knowledge sharing and training skills.
Preferred Qualifications & Skills:
- Deep experience in bioinformatics, including tools to identify relevant orthologues, homologues, isoforms, and variants to support protein engineering strategies (e.g. Blast Searches).
- Practical experience in building and utilising workflows enabling efficient data re‑use.
- Proven track record of use of protein design tools (e.g., Pymol, MOE, AlphaFold or similar).
- Evidence of active engagement in external landscape and introduction of novel technologies.
Benefits:
- Competitive salary and annual bonus based on company performance.
- Healthcare and wellbeing programmes.
- Pension plan membership.
- Shares and savings programme.
- Hybrid working model via Performance with Choice programme.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, colour, religion, sex (including pregnancy, gender identity and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Protein Design & AI-Driven Engineering Scientist in Stevenage employer: GlaxoSmithKline
GSK is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Protein Design & AI-Driven Engineering Scientist role. With a strong emphasis on employee growth through learning opportunities and cutting-edge projects, you will be at the forefront of advancing molecular design capabilities. The hybrid working model and comprehensive benefits package, including competitive salary, annual bonuses, and wellness programmes, make GSK a rewarding place to build your career in a dynamic and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Protein Design & AI-Driven Engineering Scientist in Stevenage
✨Tip Number 1
Network like a pro! Reach out to professionals in the protein engineering and AI fields on platforms like LinkedIn. Join relevant groups, attend webinars, and don’t hesitate to slide into DMs for advice or insights.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving protein design and molecular biology. This can be a game-changer during interviews, giving you a chance to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of tools like Snapgene and AlphaFold. Be ready to discuss your past projects and how you’ve used these tools to solve real-world problems in protein engineering.
✨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 joining our team at GSK and contributing to cutting-edge protein engineering.
We think you need these skills to ace Protein Design & AI-Driven Engineering Scientist in Stevenage
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your PhD and any relevant industry experience, especially in protein engineering and molecular biology.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about protein design and AI-driven engineering. Share specific examples of your past work that align with our goals at GSK, and show how you can contribute to our innovative projects.
Showcase Your Technical Skills:Don’t forget to mention your proficiency in programming and data analysis tools like Python or R. We want to see how you've used these skills in real-world applications, especially in relation to construct design and protein engineering.
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 team!
How to prepare for a job interview at GlaxoSmithKline
✨Know Your Science
Make sure you brush up on your knowledge of protein engineering and molecular biology. Be ready to discuss your experience with construct design and the tools you've used, like Snapgene or AlphaFold. This will show that you're not just familiar with the theory but have practical skills to back it up.
✨Showcase Collaboration Skills
Since this role involves working closely with computational scientists and cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any projects where teamwork led to innovative solutions or successful outcomes.
✨Demonstrate Data Savvy
With a focus on data integrity and analysis, be ready to discuss your experience with data manipulation and visualisation tools like Python or Spotfire. Bring specific examples of how you've used these skills to drive project delivery or enhance workflows.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to protein design and their use of AI/ML technologies. This shows your genuine interest in the role and helps you understand how you can contribute to their goals, making you a more attractive candidate.