Digital R&D Scientist Internship
Digital R&D, High-Throughput Experimentation & AI | Metalchemy
Location: 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-based
Compensation: £2,000-£3,000 gross per month, depending on experience and technical capability
Eligibility: Exceptional MEng, MSc, PhD candidates and recent PhD graduates
Visa Sponsorship: Not available for this position
About Metalchemy
Metalchemy 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 Role
We 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 Objectives
1. Increase R&D & QC Productivity
Develop 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&D
Implement 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&D
Develop 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 Capability
Ensure 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 2
Secondary Focus: Objectives 3 and 4, progressed as time and project momentum allow
Responsibilities
Evaluate existing R&D workflows and data flows to identify bottlenecks limiting productivity and development speed
Support implementation of Design of Experiments (DoE) and high-throughput experimentation approaches
Develop, validate and deploy Opentrons workflows to support high-throughput experimentation and laboratory automation initiatives
Build automation, optimisation and data-analysis tools that scientists can use directly
Improve the accessibility, traceability and usability of scientific data
Develop automated reporting, quality-control and knowledge-management workflows
Assess opportunities for machine learning, AI and advanced optimisation methods
Develop SOPs, user guides and training materials for all implemented workflows and tools
Support implementation and adoption of new systems across the R&D team
Deliver training sessions and collect user feedback to improve usability and uptake
Work closely with scientists, leadership and external collaborators to ensure solutions are practical and widely adopted
Requirements
Essential
MEng, MSc, PhD or recent PhD graduate in Chemistry, Materials Science, Chemical Engineering, Biotechnology, Scientific Computing, Data Science, Robotics or a related discipline
Strong Python programming and scientific computing skills
Strong quantitative, analytical and problem-solving capabilities
Understanding of experimental design, statistics and optimisation
Experience working with scientific datasets and data analysis workflows
Ability to translate scientific requirements into practical software and data-driven solutions
Excellent communication, presentation and documentation skills
Ability to work independently in a fast-moving environment
Desirable
Experience 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 Like
By the end of the internship, you will have:
Delivered measurable improvements in at least one critical R&D workflow
Reduced friction between experimentation, analysis and decision-making
Implemented tools or workflows that scientists actively use
Developed SOPs, training materials and implementation plans for all major deliverables
Successfully transferred knowledge and trained team members to use new workflows independently
Demonstrated opportunities for automation and high-throughput experimentation
Improved the accessibility, usability and traceability of scientific data
Produced a roadmap for future Digital R&D and AI implementation at Metalchemy
Achieved adoption of at least one new workflow or tool within routine day-to-day activities
Strong 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 partners
Help shape the future of Digital R&D within a growing deep-tech company
Gain hands-on experience with DoE, laboratory automation, HTE, AI and advanced materials development
Take ownership of a strategic company-wide initiative
Significant responsibility and visibility from day one
Contribute to long-term capabilities that will shape how R&D is conducted across Metalchemy
Potential pathway to a permanent role based on performance and project delivery
Application Process
Application Deadline: 3 July 2026
How to Apply: Apply via the LinkedIn job listing and follow the application instructions.
Selection Process
Initial screening call
Short technical assessment
In-person interview at our Lambeth laboratory
Start 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.
