Forensic Specialisms, Lectureships & PhD Studentships

University:  The Norwich Research Park Biosciences Doctoral Training Partnership 

Closing Date: 25th November 2024

Competition Funded PhD Project (Students Worldwide) 

Every nucleated cell has the potential to identify us. We shed cells wherever we go and different types of contact result in the transfer and mixture of different cell types.

Conventional forensic DNA recovery loses information about the molecule - or cell - the DNA originated from. This information could be critical in mixed samples and establishing where a DNA molecule came from, when it was transferred, and by whom. This project will combine advances in single-cell isolation, phenotyping, and sequencing with established and novel approaches for human identification from individual cells. Using advanced cell sorting, laser capture microdissection and microfluidic approaches, the student will develop and apply methods for human identification from individual cells. 

The student will apply short-tandem repeat (STR)-based analysis methods and sequencing approaches to single cells. The project will focus on method development with translational potential for the justice system but collaboration with the Nieduszynski group will also explore STR heterogeneity in normal human biology

University:  Heriot-Watt University

Closing Date: 6th December 2024

Funded PhD Project (UK Students only) 

This PhD studentship offers a unique opportunity to contribute to the design, testing, and commercialisation of a novel mass spectrometer aimed at rapid chemical analysis of aerosols, bioaerosols, and biological materials. Leveraging advanced laser techniques, this instrument is designed to offer exceptional sensitivity and precision, supporting applications in environmental monitoring, disease detection, and forensic analysis. Working closely with Laser 2000, an industrial partner known for its laser technology and engineering expertise, the student will receive hands-on technical guidance throughout the instrument’s development, ultimately gaining specialised skills in instrument development, laser technology and advanced analytical techniques. By the end of the PhD, the student will be proficient in critical laser applications and mass spectrometry, equipping them for future roles in academia or industry. 

 This PhD studentship will run at the Edinburgh Campus of Heriot-Watt University. Please contact Prof Townsend (d.townsend@hw.ac.uk) or Dr Moon (d.moon@hw.ac.uk) 

University:  University of St Andrews

Closing Date: Applications accepted all year round

Competition Funded PhD Project (Students Worldwide) 

This project will consider if we can use phylogenetic analysis to correct for imperfections in eyewitness testimony. Eyewitness testimony from events with multiple witnesses is often inconsistent and sometime contradictory. If we think of these inconsistencies as mutations from a common ancestor with perfect recall (but not necessarily perspective) on the event, can we obtain an objective estimate of what the collected witnesses saw? Here we will consider historical and forensic records of events with multiple witnesses, in order to construct a “family tree” of what was reported and estimate the ancestral condition. Can statistics tell us what really happened when JFK was assassinated? Could statistics inform analysis of crimes where there are multiple witnesses? Both manual and machine learning approaches will be considered.  

Closing Date:   Applications accepted all year round 

Self-Funded PhD Students Only 

Birds of prey have suffered persecution for centuries through trapping, shooting, poisoning and theft from the wild to meet the demand from egg collectors and falconers; they were also amongst the earliest beneficiaries of DNA testing in wildlife forensics. We have published the first use of massively-parallel sequencing (MPS) applied to a large body of evidential material from one of the earliest investigations. This demonstrated that our newly developed multiplex of microsatellite markers offers a huge advance over classical minisatellite DNA fingerprinting methods pioneered by Alec Jeffreys at Leicester and applied to raptors by the supervisory team in the 1990s.  

Whilst our paper described a panel of markers that could be used to profile any species of falcon, our prototype panel for Accipiters (hawks, eagles, kites etc.), the group comprising the largest radiation of diurnal birds of prey, showed more patchy success due to the greater evolutionary time depth of this family.   

In this project we propose to exploit the wealth of newly published Accipiter genomes to identify STR markers with broader taxonomic utility and build multiplexes applicable to both forensic and demographic studies of these apex predators that are key indicators of the health of ecosystems. Their sensitivity to ecological change and human persecution has caused many species to suffer population bottlenecks that have reduced genetic diversity, necessitating the identification of the most polymorphic class of markers.  

Newly identified STRs panels will be tested on our collection of pedigrees and unrelated samples to demonstrate robust genotyping before exploiting the full capabilities of MPS to type forensic traces of both degraded and mixed samples, including feathers and egg membranes that can be used to link stolen and killed birds to nest sites. 

Closing Date:   Applications accepted all year round 

 Self-Funded PhD Students Only 

The detection of new, rapidly evolving illicit drugs presents a unique challenge for laboratory analysts and public health officials. This project will explore wastewater as a means of detecting drugs of abuse to provide a more complete picture of their role in community drug use.

New Psychoactive Substances (NPS) encompass a range of synthetic, semi-synthetic, and natural drugs that have emerged over the past decades. Although they are designed to mimic the effects of traditional drugs such as heroin, cocaine, and cannabis, the rapid speed at which NPS are developed and their unknown effects present a significant threat to public health. Detection by traditional clinical and forensic techniques are challenged by these novel compounds, which are often taken in combination and which can yield ambiguous or inconclusive results.

Synthetic depressants, which include clandestinely manufactured benzodiazepines, are frequently consumed for non-medical purposes and represent one class of NPS that warrants particular attention. Speculation on their mechanism of action has been posited in various toxicological studies; however, the picture is clouded and their harms are still largely being discovered, especially in polydrug mixtures. Epidemiological studies have cited benzodiazepines as critical contributors to drug-related deaths, and it is essential that benzodiazepine use can be accurately and rapidly monitored.

This project will measure benzodiazepine levels in wastewater. The results obtained from these measurements will provide near real-time data and improve the information available on overall community health status. Additional ideas and suggestions as to the project scope are welcome.

Closing Date: Ongoing: Applicants accepted all year round

Self-funded students only 

This project involves the study of mites (Acari) in their role as useful markers in forensic investigations. 

The utility/contribution of mites in criminal investigations goes beyond crime scene investigations with dead bodies, and addresses, for example,  illegal trade, and human and animal neglect, among other topics.  We are particularly interested in investigating the role of mites in the process of decomposition of corpses and carcasses exposed to different environmental conditions; aiming to understand translocation of cadavers, burials at different depths and wrapping or concealment. 

*Candidates must have  i) knowledge of arthropods, (i.e., biology and taxonomy of at least one group), ii) basic concepts of genetics, and iii) experience in numerical analyses.  These topics will be further developed during the scholarship, with research carried out in the lab, curating forensic related collection/s, in forensic research settings or facilities, in house or abroad (e.g., taphonomy centres). 

Closing Date: Applications accepted all year round 

Self-funded students only 

 About the Project

In most criminal or forensic investigations, much of the work focuses on the collection and assessment of biological traces of human origin. Invertebrates, particularly animal micro-parts (e.g., lepidopteran scales, insect exuviae, etc) and micro-invertebrates (e.g., tardigrades) are ubiquitous in the human environment. Samples lifted from a crime scene or from human clothes will very frequently contain micro-invertebrates.

For Dr. Edmund Locard, who described for the first time the relevance of trace evidence, every contact allows the transference of material, biological or not. Since his initial work in the early 1900s, when he described sampling methods, little advance has been achieved in relation to the lifting, assessment, and analysis of micro-invertebrate traces from crime scenes.

This project aims to further our knowledge on the importance of invertebrates in crime scenes and on how we can take more advantage of this information in forensic analysis. The student will gain expertise in modern techniques developed to sample and study invertebrates from a variety of environments resembling or associated with case work, and how this can be modified and adapted to crime investigations. Main objectives will include the development of new methods of collection, analysis and interpretation of invertebrates from different substrata, like soil, clothes, from simulated crime scenes, corpses and carcasses. Experiments on different sampling methods, the production of keys for classification of animal parts and micro-invertebrates, the exploration of reliable molecular markers and numerical analyses will provide training for a future trace evidence analysis expert.

University:  University of Canterbury

Closing Date: Applications accepted all year round 

Self-funded students only 

About the Project

We’re looking for a highly-motivated PhD applicant to join our multi-disciplinary team, to work on developing a field-invariant NMR spectroscopy database for the analysis of illicit drugs.

The project

Illicit drug use is a major cause of harm, particularly for young New Zealanders. Recent research has demonstrated that drug checking services can reduce the harm caused by illicit substances by providing users and agencies with intelligence about drugs in circulation, allowing for more informed decision making. In many cases, harm is caused because users inadvertently consume a different substance to that intended, or the dosage is different to that expected. For example, in early 2021, drug checking services such as Know Your Stuff and the Institute of Environmental Science and Research (ESR) identified eutylone being distributed as MDMA and were able to connect this with severe adverse reactions in users. Early identification enabled users to make informed decisions about whether to consume substances. However, existing drug checking services cannot provide quantitative information on the composition of substances, which is key intelligence to mitigate the risks of illicit substances. This project seeks to develop automated analysis of illicit substances using Nuclear Magnetic Resonance (NMR) spectroscopy.

NMR is a powerful analytical technique that provides both identification and quantification in a single measurement. Recently benchtop NMR instruments have become available that make NMR an affordable and accessible technique. The project is a collaboration between the University of Canterbury (UC), Victoria University of Wellington (VUW), and ESR. UC has developed a new analytical tool that uses quantum mechanical (QM) modelling of the NMR signature to enable accurate quantification of mixtures of substances using benchtop NMR. VUW provides expertise in machine learning for NMR applications. While ESR provides primary analytical chemistry and forensic services for the analysis of illicit drugs in New Zealand. We are now collaborating to develop a tool for the automated quantification and identification of illicit substances, including impurities and cutting agents, using benchtop NMR. This project will focus on developing machine learning techniques to enable automated analysis of compounds in the spectral database.

University:  University of Salford

Closing Date: Applications accepted all year round 

Self-funded students only 

When we look at recent real-world applications, such as autonomous vehicle driving, use of drones to monitor events like marathons, exhibitions, processions, sports games and to study person behaviour through multiple biometric information, one can easily see that the problem is too complex and there are several open challenges. It is noted from the literature that to address such complex open issues, a single domain-based approach is not feasible. For example, use of only image information or only textual information for addressing complex challenges is not sufficient to achieve successful results. Moreover, most existing methods do not consider issues of bias and fairness. Therefore, existing methods lack effectiveness in terms of generality, robustness, consistency, reliability, fairness and unbiasedness.

The above observations motivate us to introduce intra-inter-disciplinary approaches to develop stable and reliable systems for solving complex open challenges. Different disciplines involved include image processing, pattern recognition, networking, cybersecurity, forensic, psychology, sociology, history, physics and mathematics etc. The list of challenges are as follows:

·       Multimodal approaches for domain-independent agnostic text spotting to identify persons through bib/jersey number recognition.

·       Multimodal models for Person tracking in 3D video through text spotting and image information. 

·       AI-based models for student performance prediction and understanding through handwritten document analysis.

·       AI-based techniques for photographer identification from images, for crime analysis.

·       Compressed domain-based models for deep fake/forged text and image detection.

·       Biometric signals-based models for personality traits question answering.

AI-based models for evaluating business locations, hours through person and vehicle