Digital R&D Scientist Internship

Digital R&D Scientist InternshipDigital R&D, High-Throughput Experimentation & AI | MetalchemyLocation: Lambeth, South West London (laboratory-based / in-person)Duration: Full-time fixed-term internship (13 July - 13 November 2026)Hours: Monday-Friday, 9:00am-6:00pm (42.5 hours/week)Role Split: Approximately 60% computational / 40% laboratory-basedCompensation: £2,000-£3,000 gross per month, depending on experience and technical capabilityEligibility: Exceptional MEng, MSc, PhD candidates and recent PhD graduatesVisa Sponsorship: Not available for this positionAbout MetalchemyMetalchemy is an award-winning UK deep-tech company developing and commercialising patented sustainable coatings, antimicrobial technologies and advanced materials for food packaging and other high-impact applications.Our antimicrobial and functional materials help extend the shelf life of perishable food, reducing food waste and packaging material use across supply chains. We work at the intersection of research, manufacturing, commercialisation and innovation, collaborating with customers, manufacturers, universities and industry partners to bring impactful technologies to market.We are building a next-generation Digital R&D Platform that combines Design of Experiments (DoE), laboratory automation, high-throughput experimentation (HTE) and AI-enabled workflows to accelerate innovation and improve how research translates into commercial impact.The RoleWe are looking for an ambitious, highly computational scientist or engineer to help accelerate the next generation of R&D at Metalchemy.Working directly with company leadership and scientists, you will help design and implement systems that improve how experiments are planned, executed, analysed and translated into decisions.This role is ideal for someone who enjoys combining science, software, automation and data to solve real-world R&D challenges. You will work closely with the Head of R&D, with regular check-ins to review progress and unblock technical challenges.You will help build the foundations of Metalchemy's Digital R&D Platform, creating practical tools, workflows and capabilities that increase scientific productivity, improve knowledge retention and accelerate product development across coatings, advanced materials and microbiology programmes.This is a highly visible and strategic project with significant ownership and direct impact on how innovation is conducted across the company.Successful completion of key project objectives may lead to a permanent Digital R&D Scientist, Research Automation Scientist or related role within Metalchemy.Key Project Objectives1. Increase R&D & QC ProductivityDevelop tools, workflows and automation systems that reduce repetitive manual work, improve knowledge retention and enable scientists to spend more time generating insights, solving technical challenges and advancing product development.Support automation and digitalisation of selected QC workflows, including analytical data processing, reporting and traceability.2. Establish High-Throughput, Data-Driven R&DImplement Design of Experiments (DoE), OriginPro workflows, Opentrons-enabled laboratory automation and high-throughput experimentation approaches that accelerate development cycles, improve experimental efficiency and maximise learning from every experiment.3. Build Foundations for AI-Enabled R&DDevelop the data infrastructure, workflow integrations and decision-support tools required to support predictive modelling, machine learning and future AI-assisted research, while improving the accessibility, quality and usability of scientific data across Metalchemy.4. Drive Adoption and Build Digital R&D CapabilityEnsure new tools, workflows and automation systems are successfully implemented, documented and adopted across the organisation, creating lasting capability beyond the duration of the internship.Primary Focus: Objectives 1 and 2Secondary Focus: Objectives 3 and 4, progressed as time and project momentum allowResponsibilitiesEvaluate existing R&D workflows and data flows to identify bottlenecks limiting productivity and development speedSupport implementation of Design of Experiments (DoE) and high-throughput experimentation approachesDevelop, validate and deploy Opentrons workflows to support high-throughput experimentation and laboratory automation initiativesBuild automation, optimisation and data-analysis tools that scientists can use directlyImprove the accessibility, traceability and usability of scientific dataDevelop automated reporting, quality-control and knowledge-management workflowsAssess opportunities for machine learning, AI and advanced optimisation methodsDevelop SOPs, user guides and training materials for all implemented workflows and toolsSupport implementation and adoption of new systems across the R&D teamDeliver training sessions and collect user feedback to improve usability and uptakeWork closely with scientists, leadership and external collaborators to ensure solutions are practical and widely adoptedRequirementsEssentialMEng, MSc, PhD or recent PhD graduate in Chemistry, Materials Science, Chemical Engineering, Biotechnology, Scientific Computing, Data Science, Robotics or a related disciplineStrong Python programming and scientific computing skillsStrong quantitative, analytical and problem-solving capabilitiesUnderstanding of experimental design, statistics and optimisationExperience working with scientific datasets and data analysis workflowsAbility to translate scientific requirements into practical software and data-driven solutionsExcellent communication, presentation and documentation skillsAbility to work independently in a fast-moving environmentDesirableExperience or familiarity with Design of Experiments (DoE), high-throughput experimentation (HTE), laboratory automation, scientific software development, data visualisation, machine learning, APIs, databases, workflow automation, OriginPro or related optimisation tools.Experience in coatings, formulations, materials science, nanomaterials, microbiology, antimicrobial technologies, food packaging or advanced materials would be advantageous.What Success Looks LikeBy the end of the internship, you will have:Delivered measurable improvements in at least one critical R&D workflowReduced friction between experimentation, analysis and decision-makingImplemented tools or workflows that scientists actively useDeveloped SOPs, training materials and implementation plans for all major deliverablesSuccessfully transferred knowledge and trained team members to use new workflows independentlyDemonstrated opportunities for automation and high-throughput experimentationImproved the accessibility, usability and traceability of scientific dataProduced a roadmap for future Digital R&D and AI implementation at MetalchemyAchieved adoption of at least one new workflow or tool within routine day-to-day activitiesStrong candidates may also have the opportunity to contribute to investor materials, grant applications, technical publications or intellectual property development where aligned with business priorities.The strongest outcome will be solutions that continue to be used after the project has finished and demonstrably improve the effectiveness, efficiency and scalability of Metalchemy's R&D activities.Why Join Metalchemy?Work directly with founders, scientists and industry partnersHelp shape the future of Digital R&D within a growing deep-tech companyGain hands-on experience with DoE, laboratory automation, HTE, AI and advanced materials developmentTake ownership of a strategic company-wide initiativeSignificant responsibility and visibility from day oneContribute to long-term capabilities that will shape how R&D is conducted across MetalchemyPotential pathway to a permanent role based on performance and project deliveryApplication ProcessApplication Deadline: 3 July 2026How to Apply: Apply via the LinkedIn job listing and follow the application instructions.Selection ProcessInitial screening callShort technical assessmentIn-person interview at our Lambeth laboratoryStart Date: 13 July 2026 (up to two weeks flexibility for the right candidate)This is now very close to what I'd expect from a professional deep-tech startup hiring for a strategic computational R&D role.