The purpose of this role will be to support the investigators (Dr Andrew French, Dr Michael Pound, Prof Tony Pridmore, Dr Darren Wells, Dr Jonathan Atkinson) in developing and assembling materials to support a new initiative, recently funded by UKRI/BBSRC, to provide Data Science training in the biosciences. The initiative is designed to upskill bioscience researchers in AI, data management and analytics tools, technologies and techniques. Specifically, our initiative is targeting such training at researchers working in the field of plant phenotyping, covering data analysis, capture and management. In this respect, the post is rather different from a research-led post-doctoral role, and the applicant should be motivated by a keen interest in teaching complex data-centric topics to scientists from a wide range of backgrounds and levels of experience.
The post holder will join a team developing content for a series of learning units, forming a complete course. Each topic unit has a lead academic, and the post holder will support the development of the unit, and in some cases, assist with delivery of the material. The post holder will be expected to support topics such as Python programming, image capture/analysis, machine learning and plant phenotyping. You will not need to be an expert in all these fields, but should be able to work with the topic lead (who is an expert), and be able to find and adapt material to support the learning units. Many of the training components will be delivered online, and some aspects are planned to be delivered in person (e.g. via workshops, in compliance with government and university regulations on social distancing).
Whilst different to a standard post-doctoral position that emphasizes scientific research, this role will allow the post holder to gain (further) knowledge in the content of each learning unit, in putting together material for online dissemination, in delivering material to other scientists as part of workshops, etc., and in evaluating the impacts of innovative learning experiences. The post holder will be encouraged to seek opportunities to publish novel approaches in pedagogical journals or conferences.
The project is a collaboration between the University of Nottingham and the University of Lincoln, with five investigators in Nottingham and three in Lincoln. This post is based in Nottingham, primarily at Jubilee Campus. There is a complementary post to this based at Lincoln. The successful applicant will joint the Computer Vision Laboratory in the School of Computer Science at Nottingham, home of world class research in a range of areas, including developing AI methods for plant phenotyping.
This post is fixed-term for a period of 2 years. Hours of work are full-time (36.25 hours per week), however job share arrangements may be considered.
Informal enquiries may be addressed to Andrew French, email firstname.lastname@example.org. Please note that applications sent directly to this email address will not be accepted.
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