As an interdisciplinary scientist with a background in biology and analytical chemistry, my research interests are focussed on the impact of chemicals in the environment and the interaction this chemical stress has with other environmental stressors. My expertise lies in small molecule mass spectrometry to determine chemicals found in the environment (especially in wildlife) and to determine biomarkers and pathways associated with adverse effects in exposed organisms. I am also interested in the integration of artificial intelligence within environmental toxicology to support and solve different environmental challenges. From the start of my PhD at King's College London my research was originally focussed on the uptake, biotransofrmation and elimination of pharmaceuticals in a freshwater invertebrate (Gammarus pulex) commonly found in UK rivers. I developed and validated machine learning models to predict these proccesses to support and potentially replace bioaccumulation testing during environmental risk assessments. I then moved into a postdoctoral position where I focussed on understanding the impact of pharmaceuticals by assessing behavioural disruption in these organisms. I developed and applied metabolomic workflows to gain a mechanistic understanding of animal behaviour and to link cause-effect relationships for different drug exposures. Here at Brunel, I will be working in three main areas concerned with chemical pollution. First is concerned with the determination of chemicals (and mixtures) using exposomics to characterise the chemical space in the environment, with a focus on internalised residues in animals. Second, improving mechanistic understanding of cause-effect relationships using metabolomics and lipidomics to determine biochemical changes that are phenotypically anchored. Finally, development and application of AI to support envrionmental risk assessment, replace animal testing and improve interpretation of complex datasets to better understand animal health.
Over 15,000 different per- and poly-fluoroalkyl substances (PFAS) are currently estimated to exist. Globally, over 1,000 PFAS from 382 different sub-classes have been detected in the environment, which is still likely a major underestimate, given the size of this chemical class. For humans, these chemicals have already been linked to several health issues but the risk for environmental health remains poorly understood. Importantly, the C-F bond chemistry confers significant and molecule-specific recalcitrance to natural degradation, as well as concerning potentials for accumulation and toxicity in aquatic organisms. For one substance alone, perfluorooctane sulfonic acid (PFOS), over 90% of all waterbodies tested in the UK have exceeded the environmental quality standard (EQS) of 0.65 ng/L. However, EQS only exist for PFOS which is defined for inland surface waters, other surface waters and biota. Currently, no EQS exists in the UK for groundwater, soil, sediment or for any of the other PFAS.
For public water supply, the Drinking Water Inspectorate (DWI) has set a guidance limit of 0.1 µg/L (10 ng/L) for 48 PFAS in drinking water, which water companies in England, including Affinity Water, are required to meet. Furthermore, the DWI has issued actions to water companies which have made detections of PFAS in raw water and set out a tier-based approach for impacted sources. This includes utilising catchment management source, pathway and receptor investigations for all impacted sources and the need to investigate future viability for catchment remediation, in combination with enhanced treatment solutions.
The source and fate of PFAS in the environment stems from widespread usage across multiple sectors which include products such as firefighting foams, metal plating, medicines, pesticides, textiles, automotive parts, solar panels, paints among many others. Given the widespread usage of these substances, source apportionment is complex particularly given the unique properties of PFAS which enable them to be persistent and mobile across different environmental compartments. The behaviour varies greatly for individual PFAS with some long-chain substances readily binding to solid matrices such as soil and sediment and other short-chain substances being mobile in water (i.e. surface water, groundwater). Subsequently, this behaviour leads to exposure of PFAS from air, water and soil representing a diverse risk in the environment for both public and animal health.
Significant knowledge gaps concerning the fate of PFAS have been identified which stem, in part, from limited monitoring in environmental compartments and the transformation of PFAS, that may also convert into other PFAS, further complicating monitoring and remediation efforts. To address these knowledge gaps, it is critical that monitoring in the field targets for both known and unknown PFAS to identify priority substances. Moreover, investigating how PFAS undergo degradation and/or transformation is important to better interpret monitoring data and understand potential sources of measured PFAS across catchments.
The aim of this project will be to determine the occurrence and transformation of PFAS in surface water and groundwater impacting the environment and drinking water supplies.
Eligibility
This project is an interdisciplinary collaboration between Brunel University of London and Affinity Water. The student will receive extensive multidisciplinary training in techniques to develop a valuable set of technical and theoretical expertise for a successful career as an independent scientist. The work will be approximately a 50:50 split between ‘wet lab’ and computational analysis that will develop the students’ capabilities and skillset in both areas. Importantly, the student will receive training in fieldwork, analytical chemistry and data science.
Candidates must hold an undergraduate degree (first or upper second class) or equivalent qualification in either an environmental science or analytical science discipline. A Masters qualification in a relevant discipline would be desirable but not essential. Prior experience in data analysis/visualisation, machine learning or analytical chemistry would be beneficial for the position. Applicants who have not been awarded a degree by a University in the UK will be expected to demonstrate English language skills to IELTS 7.0 (minimum 6.0 in any section). Applicants must qualify for Home tuition fees to be considered for this opportunity, more information can be found here: https://www.ukcisa.org.uk/student-advice/find-your-fee-status/.
How to apply
Please submit the documents below to thomas.miller@brunel.ac.uk by 12:00 on 27th February 2026. Interviews will take place in the beginning of March 2026
- Your up-to-date CV;
- A one A4 page personal statement setting out why you are a suitable candidate (i.e.: your skills and experience)
- Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s)
- Evidence of English language capability to IELTS 6.5 (minimum 6.0 in all sections), if applicable
- Names and contact details for two academic referees