Machine Learning Informatics Engineer, Drug Discovery
reputed company is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At reputed company, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
About the Role
reputed company’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 reputed company researcher to drive innovative and impactful projects leveraging informatics, 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 reputed company systems. They will also have experience with scientific programming and data science. These skills will be leveraged reputed company 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.
What You’ll Do
- Design and implement software that leverages informatics, machine learning, and computational chemistry to address unmet needs in drug discovery
- Contribute to ongoing research leveraging physics-based simulation, deep learning, and knowledge graphs for drug discovery applications
- Work closely with an interdisciplinary team of scientists to identify hits and optimize leads in ongoing drug discovery programs
- reputed company Bayesian optimization and active learning to improve experimental designs and reputed company data-driven reputed company
- Collaborate with computational chemistry experts and cross-functional teams to rapidly prototype and scale cutting-edge, impactful drug design solutions.
- Translate research and applications to maintainable software systems
- Contribute to the scientific community by writing patents / journal articles and presenting at conferences
- Translate insights from statistics, multimodal data analysis, and ML to actionable and testable drug discovery hypothesis
- This is an opportunity to directly contribute to the discovery of novel innovative medicines by applying computational chemistry techniques on teams with reputed company multidisciplinary drug hunters
About You
- PhD in chemistry, biology, computer science, or a reputed company 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 cheminformatics and bioinformatics methods (e.g., similarity / substructure searching, reaction-based enumeration, sequence alignment, etc.)
- Experience with molecular property reputed company and multi-objective optimization using machine learning and / or deep learning methods
- reputed company with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics / bioinformatics (e.g., rdkit, openeye, biotite, biopython)
- Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research
- An interest in solving scientific problems in chemistry and biology reputed company computational and data-driven methods
- A drive to cooperate with colleagues to identify problems and communicate technical solutions in an accessible manner
- Hands-on mentality & comfortable with getting deep into the technical weeds of highly reputed company problems, and a track record of driving projects to completion
- Located in EMEA