Research Scientist - Natural Polymers and Bio- Materials

Research Scientist - Natural Polymers and Bio-Based Materials

London, England

Materiom is seeking a full-time, hands‑on Research Scientist to support our in‑house experimental data generation efforts, developing protocols on automated platforms, and performing experiments and characterisations on bio‑based material systems and natural polymers. The goal is generating the high‑quality experimental data that drives our AI/ML‑accelerated discovery and modelling platform for sustainable polymeric materials.

• Location
  :
  London, UK
• Role Type
  :
  Full‑time, on‑site
• Salary Range
  : £40K-55K

About Materiom

Materiom is an impact‑focused, non‑profit 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 open 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 developing our next‑generation innovation platform through investments in data mining, predictive models and in‑house experimental data generation. 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

This is a hands‑on role for someone who thrives in a wet lab, particularly working with testing various polymer formulations and the properties of materials made using these formulations at different processing conditions. The role sits at the intersection of formulation science, polymer and material characterisation, and data‑driven experimental design. You will develop protocols for experimental testing with automated liquid‑handling platforms, generate clean, structured, high‑quality experimental datasets that feed directly into our machine learning workflows, and help shape the feedback loop between physical experiments and predictive models.

Key Responsibilities

• Plan and run lab‑scale formulation experiments on liquid‑based biopolymer systems including dispersions and solutions
• Characterise liquid formulations using methods such as rheology as well as spectroscopic techniques including FTIR and UV/Vis
• Prepare material samples and characterise their physical and chemical properties
• Operate and develop methods on automated liquid‑handling and high‑throughput platforms to increase experimental throughput
• Design and perform structured experiments to explore formulation and process variables efficiently and maximise the information gained from each run
• Generate clean and well‑structured datasets, ensuring data quality and integrity for downstream analysis and modelling
• Analyse and interpret experimental results to identify trends and structure–property relationships, using these insights to guide subsequent experiments
• Work within machine learning, active learning and agentic AI workflows, translating model‑guided recommendations into experiments and feeding results back into the loop
• Maintain rigorous lab records, follow good laboratory and chemical‑safety practice, create and document protocols for reproducibility
• Collaborate with internal scientists, engineers and with external partners to improve and diversify the generated experimental data
• Maintain, calibrate and troubleshoot laboratory instruments to keep experimental workflows running reliably

Required Qualifications

• PhD or MSc in Materials Science, Polymer Science, Chemistry, Chemical Engineering or a related field
• Hands‑on laboratory experience working with polymers (ideally bio‑based / natural), with a demonstrated ability to plan and run experiments and characterisations independently
• Practical experience preparing and testing end materials in various forms
• Working knowledge of Design of Experiments (DoE) and a structured, data‑driven approach to experimentation
• A genuinely hands‑on,…