PhD Studentship: Machine Learning-Based Modelling of Flavour Formation in Alternative Sources of Cocoa Aroma
Project ID: 2603 RIN
Type of studentship: PhD (4 years)
Funding Source: Fully funded 4-year PhD (BBSRC Food Consortium Industrial Doctoral Landscape Award)
Theme of project: Machine learning, flavour chemistry
Primary Host Institution: University of Reading, Department of Food and Nutritional Sciences
Secondary Institution: Imperial College London, Department of Chemical Engineering
Industry Partner: Nestlé PTC, York
Project Overview:
Sustainability challenges around cocoa resources are creating opportunities to explore alternative sources of cocoa aroma. The aim of the project is to identify sustainable alternatives to cocoa by understanding how plant‑based substrates can be roasted to create cocoa‑like flavours. This project will develop new ways to understand flavour formation during roasting using machine learning (ML) models that can predict how different ingredients and roasting conditions generate flavour compounds.
Nestlé, the world’s largest food and beverage company, produces well‑known brands across confectionery, dairy, coffee, and plant‑based foods. Central to its vision is the creation of sustainable and resilient food systems through responsible sourcing, regenerative agriculture, and science‑driven innovation. As part of this commitment, Nestlé is investing in transformative technologies that reduce pressure on agricultural raw materials while supporting affordability, nutrition, and environmental stewardship. This project aligns directly with those priorities by developing resilient, sustainable, and scalable flavour solutions that diversify ingredient options, strengthen supply‑chain robustness, and contribute to the long‑term sustainability of future food systems.
You will work at the intersection of flavour chemistry, analytical science, and machine learning. You will combine literature data with your own experimental data to build ML models to predict flavour outcomes. Through this interdisciplinary training, you will gain skills in wet‑lab flavour chemistry (GC‑MS, volatilomics, sensory science), high‑throughput experimentation, data science, and AI-assisted modelling.
By the end of the PhD, you will have developed a predictive ML surrogate model for dry-roast systems and applied it to plant‑based substrates, comparing them to cocoa. Your research will contribute to sustainable ingredient development and address global challenges linked to supply chain volatility, climate change, and the need for affordable and ethical food products.
Why choose this project?
You will join a supportive, collaborative research environment across two leading universities. At the University of Reading, you will be based in a world‑class flavour chemistry laboratory with access to advanced analytical technologies and expert mentorship. At Imperial, you will benefit from training in computational modelling, high‑performance computing (HPC), and high‑throughput automation systems.
The project offers opportunities for hands‑on experimental science, advanced modelling, and real‑world impact in one of the world’s most influential food companies. You will be part of a multidisciplinary cohort of IDLA students, benefitting from tailored professional development, entrepreneurial training, and strong peer networks.
The Food Consortium IDLA
This project is part of the Food Industrial Doctoral Landscape Award (IDLA) providing a world-class training programme combining research-led innovation with real-world industry application. It brings together 8 leading UK food manufacturers and Universities to address the challenges facing the UK food and drink sector. Students will receive high level entrepreneurial training provided by Haydn Green Institute, bespoke business training by global players in the food industry and will have free access to the IFST platform MyCPD for career development. Participating in an IDLA programme has the additional benefit that students will join an interdisciplinary cohort of students working on food sector challenges focusing on both people and planet.
The Food Consortium IDLA is committed to equality, diversity, and inclusion, welcoming applications from all backgrounds and fostering an environment where every researcher can thrive.
The student will benefit fully from the collaboration with Nestlé, including the opportunity to undertake a placement at The Nestlé Product Technology Centre (NPTC) at York during the PhD. Flexible arrangements will be available to support inclusive working and studying during the placement. The student will have access to Nestlé’s word class R&D facilities, receive training and work with relevant technologies linked to the project.
Supervisory Team:
University of Reading: Dr Dimitris Balagiannis (Primary Supervisor), Professor Jane K Parker
Imperial College London: Dr Maria Papathanasiou, Professor Karen Polizzi
Nestlé PTC: Dr Youfeng Zhang, Dr Arne Glabasnia
Start date: October 2026
Duration of award: 48 months
Terms and conditions: Fully funded for four years by Food Consortium IDLA and Nestlé. The studentship covers UK tuition fees plus enhanced annual UKRI stipend (£22,280 tax free for 2025/26 entry).
International students may apply but must cover the difference between Home and International fees which is ~£20k pa and increases annually.
Stipend and fees will be confirmed by BBSRC later in the Spring.
Candidate Profile:
We welcome applicants from a wide range of scientific backgrounds, including chemistry, chemical engineering, computational science, data science, food science or related disciplines. The successful candidate will possess a minimum 2:1 Honours degree. An MPhil, MEng, MSc or relevant industrial experience would be an advantage. Experience in any of the following is helpful but not essential: analytical chemistry, GC‑MS, reaction chemistry, Python/ML. Curiosity, problem‑solving ability, and willingness to work across disciplines are essential.
English language requirements:
Applicants must meet the minimum English language requirements.
How to apply:
- Download the application form: Click the button below to download the fillable PDF form.
- Complete the form: Open the PDF on your computer and fill in all required fields. Please do not edit the PDF structure; only complete the fields provided.
- Save your completed form: Save the file with the following naming format: IDLA [Project Code] [Your Surname] (e.g., IDLA 2603 RIN Surname.pdf).
- Submit your application: Email the completed PDF to idla@reading.ac.uk. Make sure your email subject line reads: IDLA 2603 RIN [Your Surname]
Closing date for applications: 28th February 2026