Flagship Pioneering
Lila Sciences, Inc. | Cambridge, MA ML Research Scientist, Interatomic Potential
Flagship Pioneering, Cambridge, Massachusetts, us, 02140
Overview
ML Research Scientist, Interatomic Potentials – Cambridge, MA, USA. Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by applying AI to every aspect of the scientific method, enabling solutions in human health, climate, and sustainability at unprecedented pace and scale. Learn more about this mission at www.lila.ai. We are uniquely cross-functional and collaborative, seeking individuals with an inclusive mindset and diverse thought. Our teams thrive in unstructured and creative environments where every voice is heard, because experience comes in many forms and passion matters. If this environment excites you, please apply even if you only have some of the listed experience. Your role in our Physical Sciences division focuses on developing and adapting state-of-the-art interatomic potentials for diverse material systems, integrating them into agentic AI frameworks, and connecting atomistic simulations to automated labs to drive materials discovery. Your work will help enable autonomous and intelligent scientific discovery in collaboration with machine learning and materials science experts across the company. Responsibilities
Develop, fine-tune, and deploy physics-informed interatomic potentials across crystalline, amorphous, and multi-component materials systems. Develop infrastructure for integrating interatomic potentials into scalable agentic frameworks for autonomous materials design and discovery. Collaborate with automation scientists to link simulations with high-throughput lab experiments. Partner with materials scientists, AI researchers, and platform engineers to deploy scalable simulation workflows for scientific discovery. What You’ll Need to Succeed
PhD or equivalent research/industry experience in Computational Materials Science, Computational Chemistry, Computer Science, Machine Learning, or related fields. Strong programming skills and expertise in machine learning frameworks (PyTorch, JAX, etc.). Expertise in working with machine-learned interatomic potentials, including model architecture, fine-tuning, distillation, or workflow development. Demonstrated track record in developing robust, reproducible code for interatomic potentials and frameworks. Experience in running molecular dynamics simulations and frameworks (LAMMPS, OpenMM, etc.). Familiarity with deploying models and workflows on HPC and cloud-based computing resources at scale. Strong publication record in developing and applying interatomic potentials for applications in chemical and materials sciences, with a focus on inorganic materials. Experience in working with LLM models and frameworks (HuggingFace Transformers, LangChain, Pydantic, and related toolkits). Prior work in developing agentic frameworks for atomistic simulations and/or autonomous materials discovery pipelines. Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
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ML Research Scientist, Interatomic Potentials – Cambridge, MA, USA. Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by applying AI to every aspect of the scientific method, enabling solutions in human health, climate, and sustainability at unprecedented pace and scale. Learn more about this mission at www.lila.ai. We are uniquely cross-functional and collaborative, seeking individuals with an inclusive mindset and diverse thought. Our teams thrive in unstructured and creative environments where every voice is heard, because experience comes in many forms and passion matters. If this environment excites you, please apply even if you only have some of the listed experience. Your role in our Physical Sciences division focuses on developing and adapting state-of-the-art interatomic potentials for diverse material systems, integrating them into agentic AI frameworks, and connecting atomistic simulations to automated labs to drive materials discovery. Your work will help enable autonomous and intelligent scientific discovery in collaboration with machine learning and materials science experts across the company. Responsibilities
Develop, fine-tune, and deploy physics-informed interatomic potentials across crystalline, amorphous, and multi-component materials systems. Develop infrastructure for integrating interatomic potentials into scalable agentic frameworks for autonomous materials design and discovery. Collaborate with automation scientists to link simulations with high-throughput lab experiments. Partner with materials scientists, AI researchers, and platform engineers to deploy scalable simulation workflows for scientific discovery. What You’ll Need to Succeed
PhD or equivalent research/industry experience in Computational Materials Science, Computational Chemistry, Computer Science, Machine Learning, or related fields. Strong programming skills and expertise in machine learning frameworks (PyTorch, JAX, etc.). Expertise in working with machine-learned interatomic potentials, including model architecture, fine-tuning, distillation, or workflow development. Demonstrated track record in developing robust, reproducible code for interatomic potentials and frameworks. Experience in running molecular dynamics simulations and frameworks (LAMMPS, OpenMM, etc.). Familiarity with deploying models and workflows on HPC and cloud-based computing resources at scale. Strong publication record in developing and applying interatomic potentials for applications in chemical and materials sciences, with a focus on inorganic materials. Experience in working with LLM models and frameworks (HuggingFace Transformers, LangChain, Pydantic, and related toolkits). Prior work in developing agentic frameworks for atomistic simulations and/or autonomous materials discovery pipelines. Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
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