Machine Learning Cheminformatics Engineer, Drug Discovery (EMEA) SandboxAQ’s AI Simulation group partners with global research teams to discover new drugs and materials using AI and physics-based computational solutions. We are seeking an experienced researcher to drive innovative and impactful projects leveraging cheminformatics, machine learning, and computational chemistry for drug discovery. The successful candidate will demonstrate strong abilities in cheminformatics and/or bioinformatics, including knowledge of established techniques and cutting-edge machine learning methods for modeling molecular properties and interactions with complex systems. They will also have experience with scientific programming and data science. These skills will be leveraged within a seasoned, agile, and multi-disciplinary group, including drug hunters with an excellent track record in drug discovery, computational chemists, physicists, AI experts, and software engineers.Design and implement software that leverages informatics, machine learning, and computational chemistry to address unmet needs in drug discoveryLeverage Bayesian optimization and active learning to improve experimental designs and make data-driven decisionsTranslate research and applications to maintainable software systemsContribute to the scientific community by writing patents / journal articles and presenting at conferencesTranslate insights from statistics, multimodal data analysis, and ML to actionable and testable drug discovery hypothesisPhD in chemistry, biology, computer science, or a related discipline-1-5 years of relevant experience including hands-on experience with informatics, machine learning, and computational chemistry applied to drug discovery in the private sector, like biotech or pharma- Experience with molecular property prediction and multi-objective optimization using machine learning and / or deep learning methods- Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate RandD, innovation labs, or academic research- An interest in solving scientific problems in chemistry and biology via computational and data-driven methods- Hands-on mentality and comfortable with getting deep into the technical weeds of highly complex problems, and a track record of driving projects to completion

The US base salary range for this full-time position is expected to be $142k – $198k per year. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.#