CHARM Therapeutics Hiring Computational Chemistry Candidates
CHARM Therapeutics is a biotech focused on delivering transformational medicines that will address difficult-to-drug targets in key oncogenic pathways. CHARM has developed the first highly accurate, high throughput protein-ligand co-folding algorithm (DragonFold), driven by end-to-end 3D deep learning. Our platform enables the rapid generation of highly differentiated clinical candidates, our ambition is to revolutionise drug discovery.
CHARM Therapeutics is establishing a state-of-the-art R&D facility in Cambridge, UK. We are seeking an entrepreneurial computational chemist with a passion for scientific innovation. The successful candidate will join a multidisciplinary, highly collaborative discovery team to invent novel medicines. In this role, he/she will collaborate with the AI/ML team to optimise the application of CHARM’s 3-D Deep Learning platform towards molecular design. The candidate will apply advanced computational techniques and develop innovative computational methods to design high quality molecules across target validation, hit-to-lead, and lead optimisation projects. Furthermore, he/she will engage with the external scientific community and help build CHARM’s external reputation. To accomplish the above, the successful candidate must have excellent interpersonal, cross functional collaboration and communication skills, in addition to rigorous scientific thinking.
Location: Cambridge, England, United Kingdom
Eligbility Criteria
- PhD or equivalent in computational chemistry, chemoinformatics or related quantitative fields
- Experience in an industrial/biotech setting is preferred
- The ability to apply computational chemistry methods such as virtual screening, MD, QSAR, PK/PD modelling and quantum chemistry to solve problems in a drug discovery setting
- Experience with python data analysis tools (e.g. Pandas)
- Experience with RDKit or OEChem
- Experience with FEP is highly desirable
- Fluency in python is highly desirable
- Ability to manage multiple projects simultaneously and flexibly manage priorities
- Excited about the potential of novel approaches in deep learning to solve drug discovery problems
- An understanding of related scientific disciplines pertinent to drug discovery and early development (e.g., biology, medicinal chemistry chemical, ADME, structural biology, drug safety/toxicology)
- Effective communication skills, both verbal and written
- Collaborative, with the ability to work well as part of a team
Nice-to-Have
- Experience with interrogating DEL datasets
- Experience with machine learning and deep learning frameworks (e.g. PyTorch) to solve chemical and biological data science problems
- Software development experience (e.g unit testing)
- Experience with quantum chemistry frameworks
CHARM Therapeutics Hiring
