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- Tasks: Lead computational strategies in drug discovery and collaborate with diverse scientific teams.
- Company: Innovative biotech using AI to revolutionise medicine development.
- Benefits: Competitive salary, equity options, flexible working, and clear career progression.
- Why this job: Make a real impact in drug discovery with cutting-edge computational science.
- Qualifications: PhD in relevant field and hands-on experience in computational methods.
- Other info: Strong collaboration culture with opportunities for mentorship and leadership.
The predicted salary is between 43200 - 72000 £ per year.
Location: Cambridge / Paris / Remote (EU/UK)
Team: Computational Chemistry / AI Drug Discovery
Who We Are
We’re a drug discovery biotech using computational science and AI to design better medicines, faster. Our work directly supports active drug discovery programs, and computational insights are part of everyday decision-making. We’re at a stage where our platform is proven, our pipeline is moving, and we’re now looking to strengthen senior scientific ownership across programs.
The Role
We’re hiring a Senior Computational Scientist to play a leading role in our drug discovery efforts. You’ll take ownership of computational strategy across one or more programs, working closely with medicinal chemists, biologists, and ML scientists. This role is about influence as much as execution, helping teams decide what to prioritise, what to trust, and where computation adds the most value. You won’t be managing people on day one (unless that’s your strength), but you will be expected to lead scientifically and set a high bar for quality and thinking.
What You’ll Be Doing
- Owning and shaping the computational approach within active drug discovery programs
- Designing and interpreting docking, MD, and free energy calculations to guide compound decisions
- Advising teams on the strengths and limitations of different modelling approaches
- Working closely with ML scientists to combine physics-based and AI-driven methods
- Reviewing and improving computational workflows and best practices
- Communicating results clearly and confidently in project and leadership meetings
- Mentoring more junior scientists and helping raise the overall bar
What We’re Looking For
- A PhD (or equivalent industry experience) in computational chemistry, biophysics, physics, or a related field
- Several years of hands-on experience applying computational methods in drug discovery
- Strong intuition for structure–activity relationships and molecular interactions
- Experience with industry-standard modelling tools (e.g. Schrödinger, OpenMM, GROMACS, AMBER)
- Solid Python skills for analysis, automation, and reproducibility
- Confidence engaging with experimental teams and influencing decisions
Nice to Have
- Deep experience with free energy methods
- Exposure to AI / ML approaches in molecular design
- Experience supporting programs through hit-to-lead or lead optimisation in industry
Why Join Us
- You’ll have real scientific ownership and visibility across the organisation
- Computation is treated as a strategic capability, not a service function
- Strong collaboration with experimental teams and external partners
- Competitive salary, meaningful equity, and flexible working
- Clear pathways toward principal scientist or broader technical leadership roles
Senior Computational Chemist employer: S3 Science Recruitment
Contact Detail:
S3 Science Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computational Chemist
✨Tip Number 1
Network like a pro! Reach out to professionals in the computational chemistry field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past projects and results, especially those related to drug discovery. This will help you stand out during interviews and showcase your hands-on experience.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or mentors to refine your communication skills. Being able to clearly explain your computational strategies and their impact is key in this role.
✨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 joining our team.
We think you need these skills to ace Senior Computational Chemist
Some tips for your application 🫡
Show Your Passion for Drug Discovery: When writing your application, let your enthusiasm for drug discovery shine through! We want to see how your background in computational chemistry aligns with our mission to design better medicines. Share specific examples of your work that demonstrate your commitment and expertise.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Senior Computational Scientist role. Highlight relevant experiences, especially those involving computational methods in drug discovery. We love seeing how you can influence decision-making and collaborate with teams, so don’t hold back!
Be Clear and Concise: In your written application, clarity is key! Use straightforward language to explain your skills and experiences. We appreciate a well-structured application that gets straight to the point, showcasing your qualifications without unnecessary fluff.
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 keen to join our team at StudySmarter!
How to prepare for a job interview at S3 Science Recruitment
✨Know Your Stuff
Make sure you brush up on your computational chemistry knowledge, especially around docking, MD, and free energy calculations. Be ready to discuss how you've applied these methods in past projects and how they can influence drug discovery.
✨Showcase Your Collaboration Skills
Since this role involves working closely with medicinal chemists and ML scientists, prepare examples of how you've successfully collaborated with cross-functional teams. Highlight any experiences where your input shaped project outcomes or influenced decision-making.
✨Be Ready to Discuss Tools
Familiarise yourself with industry-standard modelling tools like Schrödinger, OpenMM, GROMACS, and AMBER. Be prepared to talk about your experience with these tools and how you've used them to drive results in your previous roles.
✨Communicate Clearly
Practice explaining complex computational concepts in a straightforward manner. You’ll need to communicate results confidently in meetings, so think about how you can make your insights accessible to both scientific and non-scientific audiences.
