Location: Brighton, UK
Hours: Full‑time, up to a maximum of 1.0 FTE (37.5 hours). Flexible working options may be considered (subject to business need).
Salary: Grade 8 starting at £47,389 to £56,535 per annum, pro rata if part time.
Contract type: Fixed term contract, 30‑month duration ending 30October2028.
About the role
The University of Sussex, in partnership with Custom Pharmaceuticals Ltd (CP), offers an opportunity to develop and embed advanced data analytics and predictive modelling within pharmaceutical product development. This post is fixed‑term for 30months and is based primarily at CP Ltd’s offices in Brighton.
CP is a UK‑based contract development and manufacturing organisation that supports clients in bringing new medicines to market. The Knowledge Transfer Partnership (KTP) will support CP in establishing new in‑house capability in data analytics and quantitative modelling, enabling more systematic and reliable decision‑making across drug product development activities.
The role sits at the interface between the company and the University and is central to delivering the objectives of the partnership. At present, many development decisions rely on expert judgement and manual processes, despite the availability of large volumes of process and formulation data. The project will focus on developing and applying advanced analytical and predictive modelling approaches to improve how this data is analysed and interpreted.
Initial work will focus on early‑stage product development case studies with the aim of reducing trial‑and‑error activity, improving development success rates and shortening development timelines. Working closely with academic supervisors at the University of Sussex and multidisciplinary teams across CP, the post holder will follow CP’s New Product Introduction process to review available datasets, assess current analytical capability and design predictive models to support formulation and process decisions.
These models will be applied to optimise development activities and embedded into client‑facing workflows. A key part of the role is to consolidate the modelling and optimisation capability into outputs that demonstrate value to clients and support the first commercial launch of this new service. The post holder will lead day‑to‑day project activity, report to joint University and company governance structures and contribute to the transfer of knowledge between academic and industrial partners. The role is expected to support CP’s longer‑term strategy by embedding sustainable capability and enabling the development of new data‑driven services.
Responsibilities
- Review available datasets and assess current analytical capability.
- Lead the design and development of predictive models to support formulation and process decisions.
- Consolidate the modelling and optimisation capability into outputs that demonstrate value to clients.
- Embed predictive models into client‑facing workflows and support their optimisation during development activities.
- Lead day‑to‑day project activity and report to joint governance structures.
- Contribute to the transfer of knowledge between academic and industrial partners.
Qualifications
- Strong quantitative background in mathematics, statistics, informatics or a related discipline.
- Experience applying analytical methods to data‑intensive problems; experience in mathematical and statistical modelling, including optimisation and decision‑making under uncertainty.
- Proficiency in Python and/or R, confident in handling, analysing and interpreting large datasets.
- PhD or master’s degree with industrial experience; a PhD or equivalent research experience is desirable.
- Excellent organisational and communication skills; ability to work independently and manage competing priorities.
- Interest in research dissemination, knowledge exchange and collaborative working across academic and industrial settings.
The University of Sussex is committed to equality and valuing diversity, and applications are particularly welcomed from women and black and minority ethnic candidates, who are under‑represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex.Visa sponsorship may be available under the Skilled Worker route, and the role may also be eligible for the Global Talent visa. Prior KTP Associates may not be eligible, but this can be confirmed with the KTP Adviser.
Fixed Term Contract Duration: Fixed Term until 30October2028.
#J-18808-Ljbffr…