Lila Sciences

Company Name: Lila Sciences
Job Title: Intern, Physical Sciences Team - High Throughput XRD Analysis
Job Description: **Job Title:** Intern, Physical Sciences Team – High‑Throughput XRD Analysis **Role Summary:** Assist in developing automated workflows for high‑throughput X‑ray diffraction (XRD) data analysis, integrating processed data with machine learning models, and contributing to reproducible scientific computing practices within a multidisciplinary research environment. **Expactations:** Deliver clean, version‑controlled code that implements post‑processing of XRD data (azimuthal integration, peak detection, phase identification); integrate diffraction features into ML pipelines; produce scalable data reduction and visualization scripts; collaborate with scientists and engineers to refine analysis protocols; document workflows and maintain code quality standards. **Key Responsibilities:** - Implement and test XRD post‑processing methods, including azimuthal integration and peak analysis. - Develop scalable data‑reduction pipelines and visualizations for large diffraction datasets. - Collaborate with ML researchers to map processed diffraction features to predictive modeling workflows. - Engage in cross‑functional teamwork to design reproducible, efficient analysis procedures. - Apply best practices in coding, version control, and documentation to support team reproducibility. **Required Skills:** - Proficient in Python (NumPy, pandas, scikit‑learn). - Experience with scientific data analysis and programming. - Fundamental understanding of XRD principles: azimuthal integration, phase identification, scattering physics. - Familiarity with SQL, version control (Git), and clean coding practices. **Required Education & Certifications:** - Current enrollment in a Master’s or Ph.D. program in Physics, Materials Science & Engineering, Computer Science, or related field. - No additional certifications required, but familiarity with XRD software (pymatgen, pyFAI, VESTA, Jade) and numerical optimization libraries considered a plus.

Cambridge, United states

On site

Fresher

30-10-2025

Company Name: Lila Sciences
Job Title: Senior Data Scientist, Life Sciences
Job Description: Job Title: Senior Data Scientist, Life Sciences Role Summary: Lead the design, development, and deployment of scalable data science and software tools for laboratory data analysis. Collaborate with scientists, ML engineers, and software engineers to create reusable libraries, data pipelines, and web services that support scientific discovery and automation. Expactations: - Minimum 5 years of experience building tools/workflows in a life‑sciences environment. - Advanced proficiency in Python and version control best practices. - Strong analytical, problem‑solving, and communication skills. - Self‑motivated, detail‑oriented, and able to work autonomously in a fast‑paced setting. Key Responsibilities: - Design, implement, and maintain Python‑based scientific data services and libraries. - Work with researchers to translate experimental requirements into software solutions (e.g., LIMS, data automation). - Manage Git repositories, enforce branching strategies, code reviews, and documentation standards. - Participate in full software development lifecycle: requirements, design, coding, testing, and deployment. - Support infrastructure‑as‑code, CI/CD pipelines, and efficient deployment strategies (Kubernetes, ArgoCD, GitHub Actions). Required Skills: - Python programming (pandas, numpy, scipy) - Git workflow best practices (branching, pull requests) - Experience with scalable software design and deployment (Kubernetes, Docker) - Familiarity with web frameworks and ORMs (FastAPI, Django, SQLModel) - Workflow orchestration (Temporal, Dagster, Prefect) - Modern developer tooling (pydantic, pyright, uvicorn, poetry) - Cloud fundamentals (AWS: RDS, EC2, S3, EKS) Required Education & Certifications: - Bachelor’s or higher in Computer Science, Data Science, Life Sciences, or related field. - No specific certifications required; knowledge of relevant cloud and orchestration tools is preferred.

Cambridge, United states

Hybrid

Senior

30-10-2025

Company Name: Lila Sciences
Job Title: AI Scientist I/II - Generative Modeling for Materials Science
Job Description: **Job Title** AI Scientist I/II – Generative Modeling for Materials Science **Role Summary** Design, implement, and deploy advanced generative models (diffusion, flow‑based, geometric DL) to accelerate materials discovery. Integrate physics‑informed constraints, create robust data pipelines, and validate model outputs against experimental results, collaborating closely with software, product, and R&D teams. **Expectations** - Lead end‑to‑end model development and iterative improvement. - Translate scientific objectives into measurable data and modeling strategies. - Produce peer‑reviewed publications and technical presentations. - Operate independently with high attention to detail and strong communication. **Key Responsibilities** - Develop and train generative architectures tailored to chemical space. - Engineer physics‑informed inductive biases and sampling techniques. - Create datasets, validation frameworks, and deployment pipelines. - Partner with software engineers and product managers for production rollout. - Engage with R&D leadership and automation specialists to refine data requirements. **Required Skills** - Python programming with PyTorch or TensorFlow. - Expertise in diffusion, flow‑based, and geometric deep‑learning models. - Fundamental knowledge of materials science, physics, and chemistry. - Experience with end‑to‑end ML workflow deployment. - Strong analytical, self‑starter mindset, and excellent written/ verbal communication. **Required Education & Certifications** - Bachelor’s or higher in Materials Science, Computer Science, Physics, Chemistry, or related field. - Advanced degree (MSc/PhD) preferred, especially with a publication record in top ML (NeurIPS, ICML, ICLR) or science venues (Nature, Science, Cell Press Matter). - Optional certifications in machine learning or computational materials science.

Cambridge, United states

On site

03-11-2025

Company Name: Lila Sciences
Job Title: AI Scientist I/II - Representation Learning for Materials Science
Job Description: Job Title: AI Scientist I/II - Representation Learning for Materials Science Role Summary: Develop and deploy physics‑informed, multi‑modal representation learning algorithms that uncover fundamental relationships in materials data. Translate scientific questions into scalable, self‑supervised/unsupervised models and validate them in real‑world materials design scenarios. Expectations: - Proficient in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Strong understanding of state‑of‑the‑art representation learning, self‑supervised and unsupervised methods, and physics‑informed inductive biases, particularly geometric deep learning. - Ability to apply principles of materials science, chemistry, and physics within ML architectures. - Independent, detail‑oriented thinker capable of working with minimal supervision. - Excellent written and verbal communication; able to present technical concepts clearly. Key Responsibilities: - Design and implement novel representation learning architectures for diverse materials datasets. - Develop self‑supervised and unsupervised learning pipelines that produce meaningful material embeddings. - Collaborate with materials scientists, chemists, and software engineers to deploy models in real‑world discovery workflows. - Work with cross‑functional teams (R&D, product, automation) to translate scientific challenges into modeling strategies. Required Skills: - Advanced programming in Python and experience with end‑to‑end ML workflow deployment. - Expertise in representation learning, self‑supervised/unsupervised techniques, and physics‑informed ML. - Knowledge of geometric deep learning and inductive biases for scientific data. - Familiarity with materials science fundamentals, including chemistry and physics. - Strong analytical, problem‑solving, and independent research abilities. Required Education & Certifications: - Minimum bachelor’s degree in Materials Science, Computer Science, Physics, Chemistry, or a related field; master’s or PhD preferred. - Evidence of industry or academic experience in machine learning applied to scientific problems. - Publication record in top ML venues (NeurIPS, ICML, ICLR) and scientific journals (Nature, Science, Cell Press Matter) is highly desirable. - Experience with computational materials methods (DFT, Molecular Dynamics) and experimental materials techniques is advantageous.

Cambridge, United states

On site

03-11-2025

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