Job Post in Brief

We are seeking a part-time Computational Materials Scientist / Computational Chemist to help drive the experimentation and productization of innovative computational and machine learning approaches that accelerate the R&D and uptake of bio-based materials for net-positive impact.

• Location: London, UK
• Role Type: Part-time (0.4-0.6 FTE)
• Salary Range: £55K-70K full-time equivalent (£25K-£42K pro-rata depending on confirmed FTE)
• Application Form: https://job-boards.greenhouse.io/materiom/jobs/5028992007

About Materiom

Materiom is an impact-focused tech startup with the mission to accelerate the research, development, and uptake of bio-based materials that have a net-positive impact on the planet. We do this by building datasets and software tools for scientists, producers, and brands. The Materiom Commons is our current platform, providing a large open database of material formulations and AI features to support a community of 20,000+ scientists, designers, engineers and entrepreneurs to quickly and easily find bio-based solutions for packaging and textiles applications. We are evolving the platform through investments in data mining and predictive models, powered by new high-throughput experimental datasets from our data partners. Our interdisciplinary team blends deep expertise in circular economy, materials science, AI, and software development, and provides opportunities to learn from a diversity of perspectives. We’re creative optimists driven by a belief in collective action.

About the Role

We are seeking a Computational Materials Scientist or Computational Chemist to join our R&D team and advance the discovery and development of next-generation sustainable materials. This role bridges polymer informatics, data science, and materials engineering, with a strong emphasis on applying computational and machine learning approaches to solve real-world industry challenges.

Key Responsibilities

• Develop and apply computational models to predict structure–property–performance relationships in polymers and composites.
• Use polymer informatics tools to analyze experimental and synthetic datasets, identifying trends and guiding experimental design.
• Integrate machine learning methods into materials discovery workflows to accelerate formulation and performance optimization.
• Identify gaps in knowledge and experimental capability which can be filled via simulation or model building.
• Develop strategies for handling data challenges, including the cleaning, featurization, and standardization of heterogeneous polymer datasets to improve the reliability of predictive models.
• Collaborate with experimental scientists and engineers to validate predictions through lab testing and pilot-scale trials.
• Translate insights from computational studies into actionable recommendations for industry applications (e.g., packaging films and coatings, textiles, rigid materials or building materials).
• Infuse model insights and artefacts into software products through close collaboration with the AI engineering team.
• Maintain and document computational workflows to ensure reproducibility and scalability across projects.

Required Qualifications

• PhD or MSc in Materials Science, Materials Engineering, Polymer Science, Chemistry, Chemical Engineering, Computational Chemistry, Computer Science or a related field.
• Strong background in polymer informatics, including experience with chemical representations and featurization strategies for polymers and formulations (e.g. (Big)SMILES-based descriptors, polymer abstractions, solubility and compatibility parameters such as Hansen solubility parameters), and a solid understanding of polymer chemistry and physics.
• Demonstrated proficiency in computational modeling and at least one programming language (e.g., Python (preferred), R, MATLAB).
• Experience working with machine learning techniques for materials data (supervised/unsupervised learning, feature engineering, predictive modeling).
• Track record of collaborating with industry or applying computational methods in industrial R&D contexts.

Preferred Qualifications

• Familiarity with high-throughput experimentation, robotic platforms, or self-driving labs.
• Experience integrating multi-scale data (molecular descriptors, MD simulations, made material properties) and working with multi-modal data (including images).
• Experience incorporating scale-up or process-relevant constraints into computational or data-driven materials design.
• Excellent communication skills, with the ability to present computational insights to non-specialist stakeholders.
• Experience collaborating in small, interdisciplinary teams, using modern computational and software workflows (e.g., version-controlled code, shared notebooks, reproducible pipelines) to enable tight integration with ML and engineering partners.

What We Offer

Materiom is an impact-focused startup offering a supportive and flexible environment where you can drive the acceleration of net-positive materials using cutting-edge technology. Our benefits include

• Competitive Salary: An annual salary range of £55K-70K full-time equivalent (£25K-£42K pro-rata depending on confirmed FTE), commensurate with your experience and expertise.
• Annual Bonuses: Eligibility for performance-based bonuses to reward your contributions to the company’s success.
• Generous Paid Time Off: 30 days of paid holiday per year for full-time positions (adjusted pro-rata for part-time positions), in addition to all UK bank holidays.
• Learning & Mentorship Grants: An annual individual budget dedicated to developing your hard and soft skills.
• Commuter Support: Access to a Bike2Work scheme to support sustainable travel.
• Flexible Hybrid Working: A highly flexible scheme that includes weekly days at the office (London) and at home, as well as options for temporary remote work.
• International Retreats: Regular company retreats, often held in international locations, to build connection and celebrate progress.
• Collaborative Team Culture: Our culture is defined by deep, interdisciplinary collaboration, offering you the exciting opportunity to work at the intersection of materials science and AI to drive positive impact for people and the planet.