RA in Automated Formulation and Computational Design of Antimicrobial Delivery

Loughborough University; Loughborough; Hybride; GBP 32 000 - 39 000; Plein temps

Avantages offerts par ce poste

Hybrid working

Family-friendly support

World-class sporting facilities

Rewards and benefits

Résumé du poste

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.

Responsabilités

• 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.

Connaissances

Lab automation

Machine learning

Python

Experiment design

Interdisciplinary collaboration

Formation

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

Outils

Rheometer

Thermal analysis instruments

Description du poste

Join us and be part of a vibrant community at Loughborough University delivering high-impact science.

What you will be doing:

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

What we are looking for:

• A PhD (or close to 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).
• A background in formulation, soft materials, ionic liquids, deep eutectic solvents or gels is a plus, as is familiarity with rheology or thermal analysis.
• The ability to work independently, think across disciplines, and move comfortably between the in-lab experimentation and computation.
• Strong communication skills and a collaborative approach to working in an international team.

You don’t need to tick every box; we welcome applicants strong in either the experimental or the computational side who are keen to grow into the other.

What we offer

• A leading role in a high-impact, EU-funded international project tackling one of the greatest current global health challenges.
• Access to state-of-the-art automation and computational facilities, and the chance to build a distinctive skillset across both experimental and data-driven research.
• Collaboration with partner groups across the network, with opportunities for joint training and knowledge exchange.
• A strong launchpad for your next step. You will have the opportunity to establish a publishable dataset, gain hands-on experience with automated and machine-learning-driven discovery, make international connections, and be supported in developing fellowship and grant applications or follow-on funding.
• A supportive, interdisciplinary research environment and support for your career development.
• An excellent benefits package.

This is a full-time, fixed‑term post for 10 months, with part‑time working considered pro‑rata. Candidates who have not yet been awarded their PhD will be appointed at Research Assistant level.

For an informal discussion about the role, please contact Professor Anna Croft, [e-mail].

For more information refer to the Job Description and Person Specification.

Our Benefits

We’re committed to creating an environment where you can flourish. You’ll enjoy generous time off, including 14 university closure days and bank holidays, plus a holiday purchase scheme. Other benefits include flexible and hybrid working options, family‑friendly support, world‑class sporting facilities, and a wide range of financial, health, and sustainability perks. Discover more about our full range of rewards and benefits.

From £35,608. Subject to annual pay award.