At a Glance
- Tasks: Join our team to revolutionise drug discovery using cutting-edge computational design.
- Company: Lilly is a global healthcare leader dedicated to improving lives through innovative medicines.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a collaborative culture that values innovation and makes a real impact on health.
- Qualifications: Ph.D. or M.S. in relevant fields with hands-on experience in fragment-based lead discovery.
- Other info: Work in a dynamic environment with a focus on diversity and inclusion.
The predicted salary is between 40000 - 60000 £ per year.
At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
About Lilly: Lilly is a global healthcare leader that unites caring with discovery to make life better for people around the world. We were founded more than a century ago by a man committed to creating high-quality medicines that meet real needs, and today we remain true to that mission in all our work. Across the globe, Lilly employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to communities through philanthropy and volunteerism.
Lilly Small Molecule Discovery is an organisation purpose-built to create molecules that make life better for people. We focus on using cutting edge science to unlock new approaches that can treat people suffering from diseases with poor treatment options. We continually challenge ourselves to deliver molecules that can provide breakthrough efficacy with the highest possible safety margins. We are dedicated to optimising our mindset, technology, and processes for faster, more nimble execution. Our success is built on a culture that empowers innovative problem solving through open collaboration and individual accountability.
Discovery Technology and Platforms is a newly established function within this organisation. Its mission is to accelerate molecule discovery by building highly optimised foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and intentionally investing in novel technologies and capabilities.
About the Novel Platforms Team: The Novel Platforms team identifies and develops transformative technologies to improve hit finding, mechanism of action exploration, and molecular design. Through agile, hypothesis-driven research, we turn high-potential ideas into mature, robust platforms embedded across Lilly’s discovery organisation.
Position Summary: Lilly Small Molecule Discovery is seeking a Computational Scientist to join our Novel Platforms Fragment-based Discovery team. We are reimagining Fragment-Based Lead Discovery (FBLD) by embedding computation at its core—from data curation and modeling to design, triage, and decision-making. You will be a key contributor to an interdisciplinary initiative spanning structural biology, biophysics, chemistry, and AI systems, with the mission of transforming how fragments are discovered, evolved, and optimised. You’ll develop and integrate cutting-edge tools, to extract insight from diverse experiments—SPR, NMR, X-ray crystallography, cryo-EM, virtual screens—and convert them into actionable hypotheses. Your work will directly impact how Lilly identifies, and advances leads against challenging targets.
Key Responsibilities
- Utilise state-of-the-art software to grow, link and merge fragment hits into novel chemical designs as well as work with informaticians to develop novel methods to improve this process.
- Triage and extract key pharmacophoric and structural insights from early biophysics and fragment screening data.
- Build and improve on internal proprietary fragment libraries and develop bespoke cassette relevant to the target class being explored.
- Coordinate with internal and external chemistry resources to prioritise and ensure timely delivery of the chemical matter.
- Collaborate closely with biophysicists, structural biologists, medicinal chemists, and AI discovery teams.
Innovation & External Awareness
- Stay at the forefront of computational FBLD innovations, AI-enhanced design, and in silico fragment evolution.
- Evaluate and integrate best-in-class tools, open-source frameworks, and academic advancements.
- Drive tool adoption and best practices in fragment modeling and AI-integrated design.
Required Qualifications
- Ph.D. with 3+ years or M.S. with 5+ years of industry experience in structural biology, chemical biology, or related fields.
- Hands-on experience with software pertaining to FBLD such as Maestro/Schrodinger, ICM-Pro, GINGER, FrankenROCS, Fragmentstein, cluster4x, PanDDA, and the use of scripting to automate their use, ideally in a High-Performance Computing (HPC) environment.
- Proven track record of FBLD.
- Proven ability to independently design experiments, troubleshoot challenges, and effectively collaborate in a fast-paced environment.
Additional Preferences:
- Hands-on experience with biophysical assays for protein characterisation, binding analysis and Molecular Dynamics (MD).
- Experience in X-ray crystallography and cryo-EM data collection, processing, protein model and ligand building.
- Experience in developing methods to identify ligand-ready cryptic pockets.
- Passion for platform development, continuous optimisation, and operational excellence with a strong emphasis on data quality and reproducibility.
- Adaptability and resilience in a fast-paced, evolving research environment.
Additional Information
- Work Environment: This position’s work environment is in an office and a laboratory.
- Physical Demands/Travel: Travel up to 10% of the time.
EMBRACING DIVERSITY: Embracing diversity is at the core of our long-held value of respect for people. It is the lens through which we understand and respond to the unique needs of the millions of individuals who depend on our medicines.
For us, embracing diversity means understanding, respecting, and valuing differences, including but not limited to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other legally protected status. The greatest measure of our diversity efforts is our ability to attract and retain exceptional employees who feel comfortable in a culture that supports them being themselves.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form for further assistance.
Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
Advisor - Fragment-based Computational Design employer: Eli Lilly and Company
Contact Detail:
Eli Lilly and Company Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Advisor - Fragment-based Computational Design
✨Tip Number 1
Familiarise yourself with the specific software mentioned in the job description, such as Maestro/Schrodinger and ICM-Pro. Having hands-on experience or even a basic understanding of these tools can set you apart during discussions.
✨Tip Number 2
Network with professionals in the field of fragment-based lead discovery. Attend relevant conferences or webinars to connect with industry experts and gain insights that could be beneficial during your interview.
✨Tip Number 3
Stay updated on the latest advancements in computational design and AI-enhanced methodologies. Being able to discuss recent innovations can demonstrate your passion and commitment to the field.
✨Tip Number 4
Prepare to showcase your problem-solving skills through examples from your past experiences. Highlighting how you've tackled challenges in a fast-paced environment will resonate well with the team at Lilly.
We think you need these skills to ace Advisor - Fragment-based Computational Design
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in computational design and fragment-based lead discovery. Use specific examples that demonstrate your expertise in software like Maestro/Schrodinger and your ability to collaborate across disciplines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for the role and how your background aligns with Lilly's mission. Mention specific projects or experiences that showcase your skills in structural biology and AI-enhanced design.
Highlight Key Qualifications: Clearly outline your qualifications, especially your Ph.D. or M.S. in relevant fields and any hands-on experience with biophysical assays or X-ray crystallography. This will help you stand out as a strong candidate.
Proofread and Edit: Before submitting your application, thoroughly proofread your documents for any errors. A polished application reflects your attention to detail and professionalism, which are crucial in a scientific role.
How to prepare for a job interview at Eli Lilly and Company
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with software relevant to Fragment-Based Lead Discovery (FBLD). Highlight specific tools you've used, such as Maestro or Schrodinger, and be ready to explain how you've applied them in past projects.
✨Demonstrate Collaborative Skills
Since the role involves working closely with biophysicists, structural biologists, and chemists, share examples of successful collaborations from your previous roles. Emphasise your ability to communicate complex ideas clearly and work effectively in interdisciplinary teams.
✨Stay Updated on Industry Innovations
Research recent advancements in computational FBLD and AI-enhanced design. Being able to discuss current trends and how they could apply to Lilly's work will show your enthusiasm for the field and your commitment to continuous learning.
✨Prepare for Problem-Solving Scenarios
Expect questions that assess your problem-solving abilities. Prepare to discuss specific challenges you've faced in your research and how you approached them. Use the STAR method (Situation, Task, Action, Result) to structure your responses.