SLS Services Limited
Are you an experienced Staff Computational Chemist with a passion for designing real molecules and seeing them made within days, not months? Do you thrive at the intersection of CADD, AI-driven design, and automation? This is a rare opportunity to join a pioneering deep-tech company where your work directly shapes the future of drug discovery. We are looking for a Staff CADD Scientist to take ownership of computational strategy, integrating cutting edge simulation and machine learning into a platform that closes the design-make-test loop at unprecedented speed. The Employer Our client is a Series B deep tech company transforming chemical discovery by combining AI, robotics, and the largest ever growing database of chemical programs. Their state of the art robotic facility in Glasgow provides a high throughput bridge from in silico models to physically synthesised compounds, giving scientists a unique ability to turn design into reality faster than traditional pharma methods. With a San Francisco base (hybrid) and UK site, this is an ambitious, impact driven environment at the forefront of AI and chemistry. Qualifications & Experience PhD (or equivalent) in Computational Chemistry, Structural Biology, Biophysics, Physics, or related discipline. 8+ years hands on experience in CADD for small molecule drug discovery, including strategy ownership and delivery. Expertise across structure and ligand based design plus proficiency with MOE, OpenMM/GROMACS/AMBER, PyMOL. Strong Python skills and experience with cheminformatics toolkits (RDKit, OpenEye), GPU accelerated workflows, and cloud/HPC. Familiarity with modern ML for molecular design (GNNs, generative models) and understanding of when they complement traditional methods. Proven leadership and experience presenting complex computational reasoning to chemists and partners. Responsibilities You will: Lead computational strategy on drug discovery programmes from hit discovery through lead optimisation. Design and prioritise molecules for synthesis; partner with chemists on SAR driven hypotheses and MPO. Apply CADD methods, docking, pharmacophore, shape and 3D similarity, MD, FEP, QSAR, blending physics and ML based approaches. Help develop a reproducible, API driven computational platform and cost efficient GPU/HPC pipelines. Mentor junior scientists, influence hiring, and represent the business externally across conferences and partnerships. Skills / Technical Competencies Advanced command of ligand and structure based design workflows. Proficiency with CADD toolkits, molecular dynamics, and QSAR. Strong programming in Python, cheminformatics libraries, and experience with production level pipelines. Cloud/HPC workflow management and GPU acceleration. Nice to Haves: Hands on FEP experience (FEP+, OpenFE). Practical use of generative chemistry models and active learning in iterative design loops. Experience integrating CADD tools into API first platforms and MLOps environments. Contributions to peer reviewed publications or open source projects in CADD.
Are you an experienced Staff Computational Chemist with a passion for designing real molecules and seeing them made within days, not months? Do you thrive at the intersection of CADD, AI-driven design, and automation? This is a rare opportunity to join a pioneering deep-tech company where your work directly shapes the future of drug discovery. We are looking for a Staff CADD Scientist to take ownership of computational strategy, integrating cutting edge simulation and machine learning into a platform that closes the design-make-test loop at unprecedented speed. The Employer Our client is a Series B deep tech company transforming chemical discovery by combining AI, robotics, and the largest ever growing database of chemical programs. Their state of the art robotic facility in Glasgow provides a high throughput bridge from in silico models to physically synthesised compounds, giving scientists a unique ability to turn design into reality faster than traditional pharma methods. With a San Francisco base (hybrid) and UK site, this is an ambitious, impact driven environment at the forefront of AI and chemistry. Qualifications & Experience PhD (or equivalent) in Computational Chemistry, Structural Biology, Biophysics, Physics, or related discipline. 8+ years hands on experience in CADD for small molecule drug discovery, including strategy ownership and delivery. Expertise across structure and ligand based design plus proficiency with MOE, OpenMM/GROMACS/AMBER, PyMOL. Strong Python skills and experience with cheminformatics toolkits (RDKit, OpenEye), GPU accelerated workflows, and cloud/HPC. Familiarity with modern ML for molecular design (GNNs, generative models) and understanding of when they complement traditional methods. Proven leadership and experience presenting complex computational reasoning to chemists and partners. Responsibilities You will: Lead computational strategy on drug discovery programmes from hit discovery through lead optimisation. Design and prioritise molecules for synthesis; partner with chemists on SAR driven hypotheses and MPO. Apply CADD methods, docking, pharmacophore, shape and 3D similarity, MD, FEP, QSAR, blending physics and ML based approaches. Help develop a reproducible, API driven computational platform and cost efficient GPU/HPC pipelines. Mentor junior scientists, influence hiring, and represent the business externally across conferences and partnerships. Skills / Technical Competencies Advanced command of ligand and structure based design workflows. Proficiency with CADD toolkits, molecular dynamics, and QSAR. Strong programming in Python, cheminformatics libraries, and experience with production level pipelines. Cloud/HPC workflow management and GPU acceleration. Nice to Haves: Hands on FEP experience (FEP+, OpenFE). Practical use of generative chemistry models and active learning in iterative design loops. Experience integrating CADD tools into API first platforms and MLOps environments. Contributions to peer reviewed publications or open source projects in CADD.