Computational Scientist Abingdon, England
Job description
Evotec is a leader in integrated pharmaceutical research and development and has built substantial drug discovery expertise and technical capabilities that can drive innovative small molecules and a range of other modalities into the clinic. In addition, Evotec has built a deep internal knowledge base in key therapeutic areas including neuroscience, pain, immunology, respiratory, women’s health, aging, fibrosis, dermatology, inflammation, oncology, metabolic and infectious diseases. Leveraging these skills and expertise, Evotec successfully delivers on superior science-driven discovery alliances with pharmaceutical and biotechnology companies.
Evotec’s global Molecular Architect Department within the Molecular Discovery function is made up of around 50 people based at Abingdon (UK), Toulouse (France), Verona (Italy) and Princeton (USA). We use all available data and advanced tools to drive early adoption and design, combined with experience and knowledge, to accelerate the drug discovery process, making the right decisions to reduce the risk of late-stage attrition.
To efficiently support and expand our business at our site in Oxfordshire (UK), we are seeking a highly skilled and motivated Computational Scientist, with expertise in Python programming to join Molecular Architects. The successful candidate will be based in our flagship building at 95 Milton Park, Abingdon, where hybrid working is an option.
Role and Responsibilities
- Contribute to the development of our computational chemistry pipeline by coding, testing, and documenting new or improved features in collaboration with colleagues in our In Silico R&D department
- Interact with users of pipelines to discovery their requirements and seek their feedback
- Apply and mentor others in the application of these workflows, tools and strategies to support integrated drug discovery projects
- Use your drug design expertise to positively impact on internal and partner projects
- Constructively interact with multidisciplinary teams of drug discovery scientists (chemists, biologists, DMPK scientists, biophysicists, and data scientists)
- Identify and apply the most appropriate ligand- and structure-based methods to design and prioritize compounds throughout the different phases of a discovery project
- Present your work and results at project team meetings (internal and with partners) and at departmental meetings
- Publish research findings in peer-reviewed journals and patents and present them at scientific conferences
Education, Experience and Essential Skills
- PhD in computational chemistry, cheminformatics, structural bioinformatics, molecular modelling, or related discipline
- Very good Python skills with a working knowledge of some or all of the following: pandas, scikit-learn, conda, jupyter, git and open-source code such as RDKit
Desirable Skills and Expertise
- History of contributing to GitHub repositories
- Experience in developing or applying AI/ML tools to drug discovery problems (e.g. predictive modelling and generative design)
- Familiarity with data pipelining tools e.g. KNIME and using Linux HPC environments
- Demonstrated experience in the following areas: ligand- and structure-based drug design, virtual screening, MD, QSAR/QSPR modelling, QM calculations, protein modelling
- Expertise in the use of commercial modelling software e.g. from CCG, OpenEye, Cresset and the CCDC
- Understanding of medicinal chemistry principles and drug discovery concepts
- A collaborative outlook with a track record of innovation and problem-solving
- An ability to work on multiple projects in parallel and deliver high-quality results
- Thrive on a variety of challenges in a fast-moving environment
- Excellent communication skills, with fluent English (oral and written)
Job Types: Full-time, Permanent
Salary: From £37,400.00 per year
Benefits:
- Casual dress
- Company events
- Company pension
- Cycle to work scheme
- Discounted or free food
- Employee discount
- Flexitime
- Free parking
- On-site parking
- Private dental insurance
- Private medical insurance
- Referral programme
- Wellness programme
- Work from home
Schedule:
- Flexitime
Supplemental pay types:
- Performance bonus
- Yearly bonus
Ability to commute/relocate:
- Abingdon: reliably commute or plan to relocate before starting work (required)
Work Location: Hybrid remote in Abingdon
Reference ID: 06801
