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Computer-aided drug design (cadd) software developer

Glasgow (Glasgow City)
Software developer
Posted: 14 November
Offer description

About Chemify Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world’s largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity. Job Description: We are looking for an enthusiastic and motivated Computer-Aided Drug Design (CADD) Software Developer to help build and enhance our next-generation platform. You’ll be joining a dynamic, cross-disciplinary team of computational scientists, chemists, medicinal chemists, software engineers, data engineers, and AI researchers dedicated to accelerating the discovery of new molecules. This is an exciting opportunity to grow your skills in a fast-paced, innovative environment. You'll be eager to learn, ready to tackle interesting scientific challenges with guidance from senior colleagues, and excited to collaborate closely to create powerful, intuitive tools for drug design. Our software and robotic platforms empower scientists to design and analyze novel therapeutic candidates. You will contribute to developing and integrating CADD methodologies into a cohesive, user-friendly application suite. We are looking for someone with a solid foundation in software development (especially Python), a passion for science, and a desire to build tools that make a real-world impact. If you are passionate about solving problems at the intersection of chemistry, computer science, and medicine and are energized by learning from experienced scientists and engineers, we’d love to have you join our team. Key Responsibilities: Collaborate with senior developers and scientists to translate scientific requirements into well-defined software features. Assist in the full lifecycle of feature development, from design discussions and implementation to testing and deployment, under the guidance of senior team members. Write clean, well-tested, and maintainable code for our molecular modeling, virtual screening, and predictive modeling tools. Support the integration of computational workflows, ensuring they run efficiently on our cloud and high-performance computing (HPC) environments. Learn and apply best practices for scientific software development, including code documentation, validation, and ensuring the reproducibility of results. Actively participate in team-wide initiatives, including code reviews, design discussions, and evaluating new tools and technologies. What you’ll bring: Bachelor's or Master's degree in Computer Science, Computational Chemistry, Cheminformatics, Physics, Biophysics, or a related field with a strong interest in molecular science. Solid programming skills in Python, developed through academic, personal, or internship projects. Familiarity with scientific computing and data science libraries (e.g., NumPy, SciPy, Scikit-learn, RDKit). A genuine passion for science and a strong desire to apply computer science skills to problems in drug discovery. A collaborative mindset, strong communication skills, and the ability to work effectively within a cross-disciplinary team. Excellent problem-solving skills and a proactive, can-do attitude. An eagerness to learn new scientific concepts, computational methods, and software engineering practices from experienced mentors. Basic understanding of version control with Git. Beneficial Skills: Familiarity with a core cheminformatics toolkit such as RDKit. Exposure to building backend services or APIs, particularly with Python frameworks like FastAPI. Basic knowledge of C/C++ or an interest in high-performance computing. Familiarity with containerized applications (Docker) and CI/CD principles. Some experience with relational databases (e.g., PostgreSQL) and writing SQL queries. An interest in machine learning (especially deep learning, GNNs, or generative models) applied to chemical or biological data. Exposure to molecular modeling software and libraries (e.g., OpenMM, GROMACS, Amber, PyMOL). A portfolio of projects or open-source contributions (e.g., a GitHub profile) that demonstrates your skills and passion for software development.

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