Machine Learning Engineer

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We are seeking a full-time Engineer in Machine Learning to join Dr Vince Smith's Diversity and Informatics Division at the Natural History Museum, as part of SUMMIT (Scaling Up Museum Machine-learning and Intelligence Technologies). This three-year funded programme will explore the application of computer vision and machine learning technologies to increase the scope, scale and speed of strategically critical research programmes. This will deliver a step-change in NHM activities that are helping to map a sustainable future for humanity and Earth's ecosystems on which we all depend.

The successful applicant will join the Software Engineering team and contribute to the critical mass of expertise necessary to develop a portfolio of machine learning, big data and AI digital capabilities that accelerate major NHM research programmes. Five project topics have been identified, based on current priorities and software development activities: applying AI/ML to automate digitisation workflows; taxonomic and phenotypic data extraction (data mining) from digitised literature and specimen images; AI-powered datamining workflows to support planetary health indicators; in-situ acoustic and visual species identification to develop biological monitoring devices; and automating landmark placement to scale-up generation and analytics of our 3D specimen imaging.

The post holder is expected to follow Machine Learning (ML) and Deep Learning (DL) methodologies, identifying where their application could best advance our targeted areas of research and delivering associated software to accelerate these research programmes. Domain knowledge in the biological and Earth sciences is not expected and will be provided by the wider research teams associated with each area of application.

The role is expected to produce innovative and novel research software, to be published as papers in leading conferences and peer-reviewed journals