Hello,
A 4 year fellowship for a computer scientist is available in the Intelligent Data Analysis team at Kew Gardens - we manage one of the world's largest scientific plant and fungal specimen collections and associated data. Our scientific work over the past decades - and centuries - has assembled labelled datasets which we can now reposition as training data for machine learning applications. This fellowship will develop this area to research and develop advanced techniques to mobilise the data and integrate it with complementary datasets from other organisations, and therefore may be of interest to members of the open-GLAM community.
* Fellowship details: https://www.kew.org/sites/default/files/2019-11/Kew%20Future%20Leaders%20Fel...https://slack-redir.net/link?url=https%3A%2F%2Fwww.kew.org%2Fsites%2Fdefault%2Ffiles%2F2019-11%2FKew%2520Future%2520Leaders%2520Fellowship.pdf&v=3 * Intelligent Data Analysis team: https://www.kew.org/science/our-science/departments/biodiversity-and-spatial...https://slack-redir.net/link?url=https%3A%2F%2Fwww.kew.org%2Fscience%2Four-science%2Fdepartments%2Fbiodiversity-and-spatial-analysis%2Fintelligent-data-analysis&v=3 * Kew science: https://www.kew.org/sciencehttps://slack-redir.net/link?url=https%3A%2F%2Fwww.kew.org%2Fscience&v=3 For any open-GLAM members using twitter who want to send this to their followers, a link to a tweet publicising the vacancy is here: https://twitter.com/nickynicolson/status/1202555246179995648
Initial informal discussions via email are welcome. Application deadline is 2020-01-17.
cheers, Nicky
Dr Nicky Nicolson Senior Research Leader, Biodiversity Informatics RBG Kew Jodrell Laboratory, room 2.51 Tel: +44 20 8332 5712 ORCID: 0000-0003-3700-4884http://orcid.org/0000-0003-3700-4884 Twitter: @nickynicolsonhttps://twitter.com/nickynicolson
Royal Botanic Gardens, Kew: Kew operates across two sites: Kew Gardens in south-west London, a UNESCO World Heritage Site, and Wakehurst in West Sussex, which is home to Kew's Millennium Seed Bank. Kew also has a permanent research station in Madagascar, one of the world's biodiversity hotspots. With over 300 scientists, Kew has an extensive research programme that includes a wide range of projects - from the analysis of genomes to the discovery and identification of new species and the impact of climate change on the wild relatives of crops.
Kew's Science Strategy (2015-2020) outlines our scientific vision to document and understand global plant and fungal diversity and its uses, bringing authoritative expertise to bear on the critical challenges facing humanity today. It sets out three strategic priorities for Kew Science:
1. To document and research global plant and fungal diversity and its uses for humanity. 2. To curate and provide data-rich evidence from Kew's unrivalled collections as a global asset for scientific research. 3. To disseminate our scientific knowledge of plants and fungi, maximising its impact in science, education, conservation policy and management.
https://www.kew.org/sciencehttps://www.kew.org/science https://www.kew.org/science/our-science/publications-and-reports/science-rep...https://www.kew.org/science/our-science/publications-and-reports/science-reports/kew-science-strategy https://www.kew.org/science/our-science/publications-and-reports/science-rep...https://www.kew.org/science/our-science/publications-and-reports/science-reports/kew-collections-strategy
Biodiversity Informatics and Spatial Analysis The Biodiversity Informatics and Spatial Analysis department apply computational techniques to analyse, edit, curate, organise, mine and disseminate data to evaluate trends and patterns through time and space.
https://www.kew.org/science/our-science/departments/biodiversity-and-spatial...https://www.kew.org/science/our-science/departments/biodiversity-and-spatial-analysis
Intelligent data analysis
The Intelligent Data Analysis team, led by Dr Nicky Nicolson, specialise in the use of computational techniques such as clustering, classification and network, image and text analysis to develop a rich data model to enhance the use of, and accessibility to, Kew's priceless physical and digital collections. These collections provide a huge evidence base to support species discovery and conservation, and can help us to answer fundamental questions about the ecology and evolution of the world's plants and fungi.
Kew holds a rich array of scientific information in the form of structured data, images and texts. These resources cover the range of stages in the process of describing species: field collection, specimen identification and distribution, and the publication of scientific results and datasets. These datasets can be mined for entities and relationships to form a more interconnected data model - to unlock a rich evidence base in support of plant and fungal science. The Intelligent Data Analysis team work collaboratively with colleagues across similar collections-based organisations, as well as data mobilisation programmes such as the Global Biodiversity Information Facility and the Biodiversity Heritage Library.
This Fellowship provides a unique opportunity for a computer scientist to use Kew's vast collections as training data for machine learning applications to answer novel applied computational research questions. These training data are supported by motivated plant and fungal experts who are best placed to validate and explore results.
They would like to hear from motivated applicants with specialist knowledge in scientific programming and use of toolkits and libraries in areas such as AI and machine learning, data manipulation, exploration and cleaning, data summarisation and visualisation.
https://www.kew.org/science/our-science/departments/biodiversity-and-spatial...https://www.kew.org/science/our-science/departments/biodiversity-and-spatial-analysis/intelligent-data-analysis
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The Royal Botanic Gardens, Kew is a non-departmental public body with exempt charitable status, whose principal place of business is at Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AE, United Kingdom.
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