Research Assistant - Automated Formulation & ML-Driven Gels

Loughborough University; Loughborough; Hybrid; GBP 32,000 - 39,000; Full time

Benefits offered by this job

Hybrid working

Family-friendly support

World-class sporting facilities

Rewards and benefits

Job summary

Loughborough University is seeking a researcher to adapt formulation methods for gelation and rapid screening, building a rich data-driven understanding of gels. You will combine experimental work with computational modelling and ML to optimise formulations, collaborating across international partners and contributing to impactful health-related outcomes.

The role offers access to state-of-the-art automation and computing facilities, with a strong emphasis on interdisciplinary training and

Qualifications

• PhD (or near completion) in chemistry, chemical engineering, materials science, soft matter physics, computational chemistry, or a related discipline.
• Hands-on experience with laboratory automation or high-throughput experimentation, and/or strong skills in computational modelling or machine learning (Python experience is highly desirable).
• Background in formulation, soft materials, ionic liquids, deep eutectic solvents or gels; familiarity with rheology or thermal analysis.
• Ability to work independently, think across disciplines, and move comfortably between in-lab experimentation and computation.
• Strong communication skills and a collaborative approach to working in an international team.

Responsibilities

• Adapt formulation methods for on-platform gelation and rapid functional assessment using automated screening.
• Prepare and characterise gels, including rheology, viscometry and thermal analysis, to build a high-quality experimental property database.
• Integrate experimental and computational data to build predictive models and identify promising new formulations.
• Use machine learning to optimise gels across a range of functional parameters.
• Collaborate with partners across the globe to align your results with project needs and present findings.

Skills

Lab automation

Machine learning

Python

Experiment design

Interdisciplinary collaboration

Education

PhD (or close to completion) in chemistry or related field

Tools

Rheometer

Thermal analysis instruments

Job description

Loughborough University is seeking a researcher to adapt formulation methods for gelation and rapid screening, building a rich data-driven understanding of gels. You will combine experimental work with computational modelling and ML to optimise formulations, collaborating across international partners and contributing to impactful health-related outcomes.

The role offers access to state-of-the-art automation and computing facilities, with a strong emphasis on interdisciplinary training and