Research Scientist, Computational Condensed Matter Physics

About the Role

This Research Scientist position in Computational Condensed Matter Physics at LILA Sciences represents a unique opportunity to drive innovation at the intersection of fundamental physics and practical materials discovery. The role demands deep expertise in applying computational methods to accelerate the development of advanced materials. You will leverage first-principles modeling, atomistic simulations, and cutting-edge AI/ML techniques to tackle challenging problems in quantum materials, superconductors, and next-generation electronic devices. This position requires a scientist who can bridge theoretical understanding with computational implementation to generate tangible discovery outcomes. You will operate within a dynamic, interdisciplinary environment where computational insights directly inform experimental direction and hypothesis generation. The role is designed for an individual capable of translating complex physical phenomena into actionable computational strategies that drive material innovation forward.

What You'll Do

Your daily responsibilities will center on applying computational condensed matter physics to accelerate materials discovery and optimization. You will utilize electronic structure calculations and phonon simulations to investigate the properties of quantum materials, superconductors, and electronic devices. A core function will be establishing direct connections between simulation outputs and experimental observations, thereby developing workflows that close the loop between computation and experimental validation. You will build predictive models derived from both computational and experimental data streams to guide materials selection and optimization strategies. Analyzing simulation and experimental data to generate actionable materials hypotheses will be a central task. You will partner closely with machine learning specialists, software engineers, and experimental teams to develop integrated discovery workflows. Finally, you will be responsible for clearly communicating complex physical insights, model limitations, and data-driven recommendations to cross-functional collaborators across physics, AI, and experimental domains.

Requirements

To succeed in this role, you must possess a PhD or equivalent experience in Physics, Materials Science, Chemistry, Applied Mathematics, or a closely related quantitative field. A strong foundation in computational condensed matter physics, electronic structure theory, and atomistic simulation methodologies is essential. You require a deep understanding of electronic-structure theory, including quantum chemistry, Density Functional Theory (DFT), and beyond-DFT methods, specifically regarding their application to electronic, magnetic, and quantum materials. Demonstrated experience applying first-principles or atomistic methods to materials discovery, optimization, or fundamental understanding is required. Familiarity with complex material classes such as superconductors, quantum materials, electronic materials, semiconductors, or other device-relevant systems is necessary. Strong programming proficiency in Python and robust scientific computing workflows is non-negotiable. You must possess the ability to work effectively within collaborative, interdisciplinary research environments and manage multiple computational and experimental data streams simultaneously.

Qualifications and Preferred Experience

While the core requirements establish the baseline qualifications, certain additional experiences significantly strengthen candidacy. Experience working with amorphous materials and performing vibrational properties calculations demonstrates valuable specialization. Advanced expertise in electronic structure methods beyond standard DFT approaches is highly regarded. Familiarity with applying AI/ML techniques specifically to computational materials science or physics-based simulation data is increasingly important. Experience with agentic AI systems, autonomous scientific workflows, or simulation-aware agents represents a significant advantage. A background focused on quantum materials, superconductors, semiconductors, or electronic device materials directly aligns with LILA's research priorities. Prior experience integrating computational predictions with experimental characterization, device measurements, or closed-loop optimization workflows is strongly valued. Finally, the ability to distill complex technical concepts, clearly articulate model limitations, and communicate physical insight to cross-functional collaborators across diverse scientific domains is essential for success in this role.

Compensation and Practical Information

LILA offers competitive base compensation structured with bonus potential and generous early-stage equity participation, with final offers reflecting background, expertise, and expected impact. U.S. full-time employees receive comprehensive benefits including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with company-wide holidays; paid parental leave; educational assistance; commuter benefits including bike share memberships; and a company-subidized lunch program. International employees outside the U.S. receive benefits structured according to regional requirements. This role is based in Cambridge, MA, USA, operating full-time. Practical considerations regarding work authorization, visa sponsorship, and employment terms will be confirmed during the hiring process in compliance with applicable laws and company policies.