RA in Automated Formulation and Computational Design of Antimicrobial Delivery

Economics Network; Loughborough; Ibrido; GBP 32.000 - 39.000; Tempo pieno

Vantaggi offerti da questo lavoro

Excellent benefits package

Hybrid working options

Descrizione del lavoro

Loughborough University seeks a researcher to advance gel formulation science within an EU-funded international project. The role combines experimental and computational work across interdisciplinary teams, focusing on automated screening, rheology, and data-driven discovery.

You may be at the final stages of your PhD or recently awarded, with strengths in either experimental or computational approaches, and a desire to grow in the other area.

Competenze

• 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 desirable).
• Background in formulation, soft materials, ionic liquids, deep eutectic solvents or gels is a plus; familiarity with rheology or thermal analysis.
• Ability to work independently, cross-disciplinary thinking, and balance in-lab experimentation with computation.
• Strong communication and collaboration in an international team.

Mansioni

• 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 results with project needs and present findings.

Conoscenze

Lab automation

High-throughput screening

Computational modelling

Machine learning

Formazione

PhD in Chemistry/Materials Science/Chemical Engineering/Soft Matter

Strumenti

Python

Descrizione del lavoro

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

Here’s more about the role and what we’re looking for:

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 moreabout our full range of rewards andbenefits.

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