Plastic pollution and in particular microplastics (< 5 mm) are a major problem across the globe, affecting oceans, freshwater, soil and organisms but also found in human blood, food and livestock. Because of the widespread of microplastic pollution on Earth and near-permanent contamination of environments, microplastic pollution could be one of the main anthropogenic changes on Earth. Concerns are now emerging regarding the effect of microplastic on microbial communities, with microplastics acting as vehicles for microorganisms and representing potential unique microbial niches. Furthermore, antimicrobial resistances (AMR) are of particular concern, because antimicrobial resistance stressors such as antibiotics and heavy metals and other chemicals can bind to plastic and could lead to the increase in AMR prevalence in the environment and contribute to their dispersion. Organic waste-derived materials (e.g. compost, anaerobic digestate and sludge) by their use (e.g. fertiliser), can represent direct entry point for microplastics into the environment and furthermore sludge contain high levels of AMR. In parallel, detection and quantification of microplastics in environmental samples (e.g. soil, sludge) is extremely difficult, time consuming and without standardised protocols. However, detection and quantification of microplastics is critical to determine their distribution in the environment and the extent of their effect on microbial communities.
The project would aim i) to design new monitoring system based on optical sensors technology coupled with novel artificial intelligence algorithms, for autonomous, and rapid detection of microplastics in environmental samples, ii) quantify microplastics in sludge and soil receiving sludges with the new technology and established protocols, iii) assess the microbial community associated with microplastics, and iv) determine if microplastics affects antimicrobial resistance in sludges and soil receiving sludges using culture dependent and independent methods. Outcomes from this research will help us to assess the extent of microplastics distribution in such samples, how it could affect microorganisms and spread AMR, and to directly inform environmental protection agencies to consider for future update in legislation.
This exciting project is a collaboration between the School of Applied Sciences (lead), and the School of Computing, Engineering & the Build Environment at Edinburgh Napier University (ENU). The successful student will gain a variety of academic and state-of-the-art research skills (e.g. sensors technology, artificial intelligence, molecular biology, next generation sequencing, quantitative-PCR, data and statistical analysis, R software, bioinformatics, scientific publications) on a multidisciplinary project. The successful candidate will be part of a dynamic postgraduate community at ENU, exposed to a range of opportunities to attend training and conference, to develop further their professional and research skills.
Academic qualifications
A first degree (at least a 2.1) ideally in microbiology/environmental microbiology/microbial ecology, computer/data science, electronic/chemical engineering with a good fundamental knowledge of techniques used to study microorganisms.
English language requirement
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.
Essential attributes:
· Experience of fundamental microbiology
· Competent in research skills, data analysis and presentation, and problem-solving
· Knowledge of molecular biology
· Good written and oral communication skills
· Strong motivation, with evidence of independent research skills relevant to the project
· Good time management
Desirable attributes:
Good statistical skills (e.g. R); familiarity with bioinformatics; background understanding in sensors, computational tools, artificial intelligence/machine learning methods.
TO APPLY PLEASE CLICK ON THE 'INSTITUTION WEBSITE' LINK ON THE RIGHT-HAND SIDE OF THIS PAGE.
When applying, please quote the application reference SAS0178 on your form.
APPLICATION CHECKLIST
· Completed application form
· CV
· 2 academic references, using the Postgraduate Educational Reference Form (Found on the application process page)
· A personal research statement (This should include (a) a brief description of your relevant experience and skills, (b) an indication of
· What you would uniquely bring to the project and (c) a statement of how this project fits with your future direction.)
· Evidence of proficiency in English (if appropriate)
For informal enquiries about this PhD project, please contact a member of the team: Dr Aimeric Blaud ([Email Address Removed] ), Dr Abdelfateh Kerrouche ([Email Address Removed]), Dr Donald Morrison ([Email Address Removed]).
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