We are seeking an enthusiastic student to pioneer the next generation of environmental modelling innovation. Sitting at the intersection of disciplines, this exciting opportunity will allow you to demonstrate how our ability to model the environment can be transformed by contemporary software architecture. You will showcase this through a case study of adapting an existing environmental exposure model to rapidly respond to risks posed by perfluoroalkyl substances (PFAS), an emerging contaminant of high concern.
Problem: Current environmental models are hindered by legacy software development practices. They are often large, monolithic codebases, making them inflexible and difficult to rapidly adapt to evolving science or risks.
Why PFAS? PFAS are widely used in products from non-stick cookware to firefighting foams. However, these “forever chemicals” are toxic to wildlife and humans, leading to significant concerns about their use. The ability to empower timely regulation and mitigation hinges on models that can accurately predict PFAS behaviour and exposure to wildlife.
Revolutionise environmental modelling: You will pioneer the use of the modern software engineering paradigm of microservices in environmental modelling. By splitting the existing model into smaller, interoperable microservices, you will the introduce the flexibility to, for instance, adapt to new contaminants, and different scenarios that might be more computational demanding. Each microservice will be responsible for individual processes (e.g. chemical transformation), communicating via standardised interfaces to form the larger model. Our case study will demonstrate how embracing microservice architecture can solve the aforementioned problems by enabling rapid extension of an existing environmental exposure model to PFAS, and more broadly to other models of the natural environment.
Students with diverse backgrounds are encouraged to apply. We welcome applicants with an undergraduate degree in any relevant discipline, such as environmental, natural, physical, chemical or computer scientists. Training opportunities will be tailored to your experience.
Candidates shall be good honours graduates in appropriate subject areas, of a recognised university or comparable university, or persons holding equivalent qualifications who show evidence of exceptional ability, or who have demonstrated their ability in graduate studies.
Email address for enquiries.
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