Research Scientist, Statistical Mechanics and Dynamics

Posted 6 Days Ago
Be an Early Applicant
Cambridge, MA
In-Office
Senior level
Biotech
The Role
The role involves designing molecular dynamics and Monte Carlo algorithms, integrating them with AI for materials discovery, and collaborating with interdisciplinary teams to advance simulation fidelity.
Summary Generated by Built In

About Lila Sciences

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 building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai    

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

Your Impact at Lila

Your role in our Physical Sciences division will focus on designing and implementing state-of-the-art simulation approaches to model transport, kinetics, rare events, and reaction networks, and integrating them with AI-driven platforms for materials discovery. Your work will be integral to our efforts in predicting, designing, and controlling the behavior of complex materials and molecular systems, and their acceleration via agentic AI. You will partner with diverse teams at Lila, including machine learning experts working on scientific superintelligence and materials science experts performing real-world experiments.

What You'll Be Building

  • Develop and extend molecular dynamics and Monte Carlo algorithms to capture rare events, non-equilibrium processes, transport phenomena, and mapping complex reaction networks.
  • Build scalable simulation workflows that integrate statistical mechanics methods with machine learned interatomic potentials and agentic AI frameworks.
  • Design methods for coupling dynamics simulations with experimental observables to enable closed-loop verification and discovery with automated labs.
  • Collaborate with computational scientists, machine learning experts, and platform engineers to advance the fidelity and scalability of simulation-driven materials discovery.
  • Establish reproducible, modular software pipelines for statistical mechanics and dynamics simulations that can be deployed on HPC and cloud-based infrastructure.

What You’ll Need to Succeed

  • PhD or equivalent research/industry experience in Physics, Chemistry, Chemical Engineering, Mechanical Engineering, Applied Mathematics, or related fields.
  • Strong background in statistical mechanics, free energy calculations, reaction mapping, non-equilibrium dynamics, and rare-event sampling.
  • Demonstrated expertise with molecular dynamics, Monte Carlo, and/or kinetic simulation software and frameworks (LAMMPS, GROMACS, OpenMM, HOOMD, etc.).
  • Solid programming skills and experience with scientific computing (Python, C/C++, MPI, CUDA, etc.).
  • Experience running and automating simulations on HPC and/or cloud environments at scale.

Bonus Points For

  • Strong publication record applying advanced statistical mechanics or dynamics simulations to molecular and materials systems, including but not limited to molecular/biomolecular systems and solid-state materials and interfaces.
  • Prior work in coupling dynamics simulations with data-driven, AI-based, and/or agentic frameworks.
  • Good familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow, etc.)
  • Prior experience working with machine learned interatomic potentials, including model training, fine-tuning, and data generation
  • Worked closely with experimental teams to extract and corroborate experimental observables from dynamics simulations

We’re All In

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.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Top Skills

C/C++
Cuda
Gromacs
Hoomd
Jax
Lammps
Mpi
Openmm
Python
PyTorch
TensorFlow
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The Company
HQ: Cambridge, MA
475 Employees
Year Founded: 2000

What We Do

Flagship Pioneering conceives, creates, resources, and develops first-in-category life sciences companies to transform human health and sustainability.

Since its launch in 2000, the firm has applied a unique, hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $30 billion in aggregate value. To date, Flagship is backed by >$3 billion of aggregate capital commitments, of which over $1.5 billion has been deployed toward the founding and growth of its pioneering companies alongside >$10 billion of follow-on investments from other institutions.

The current Flagship ecosystem includes Denali Therapeutics (NASDAQ: DNLI), Evelo Biosciences (NASDAQ: EVLO), Moderna Therapeutics (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Seres Therapeutics (NASDAQ: MCRB), and Syros Pharmaceuticals (NASDAQ: SYRS).

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