Company

Ucl - Biological SciencesSee more

addressAddressLondon, Greater London
type Form of workFull Time
salary Salary£37,099 to £42,099
CategoryIT

Job description

About us Biosciences is one of the world’s foremost centres for research and teaching in the biological sciences and one of the largest Divisions within UCL, undertaking a significant amount of research and teaching. The Division has a diverse portfolio addressing all areas of biology from protein interactions to cell function, organism development, genetics, population studies and the environment. Computational modelling approaches are frequently used alongside experimental research programmes and much of our research crosses traditional boundaries, including the relationship of biodiversity to the health of the planet. Activity is underpinned by high calibre science technology platforms and state of the art equipment. Educational activity includes a range of undergraduate programmes, an expanding number of Masters Programmes and a substantial number of postgraduate research students. This is an exciting opportunity to join a vibrant team of researchers from UCL, Natural History Museum and University of Haifa, Israel on a NERC-funded project to determine the diversity in sensory mechanisms by which wasps detect prey. There are over 100,000 described species of wasps; these include parasitoids, solitary predatory wasps and social wasps. They hunt a diversity of prey types using a range of different strategies. This project will use high-quality chromosome-level genome sequence data and sensory morphology (e.g. SEM; CTscans) data to determine the sensing machinery that has evolved across the phylogeny of wasps in relation to prey type. About the role The main purpose of this position is to provide technical support for a NERC funded project on the sensory ecology and evolution of wasps predation, using comparative analyses of genomes and morphology to identify sensory mechanisms used by wasps to detect prey. Salary is Grade 7, Spine Point 30 per annum. https://www.ucl.ac.uk/human-resources/sites/human_resources/files/2023_-_24_ucl_non-clinical_grade_structure_with_spinal_points_december_2023_update_1.2.pdf Interview Date(s) will be in early/mid January 2024. This role is an open-ended contract with a funding end date of 30/06/2026 in the first instance. This appointment is subject to UCL Terms and Conditions of Service for Academic Staff. Please visit https://www.ucl.ac.uk/human-resources/policies/2021/jun/conditions-service-academic-staff for more information. A job description and person specification can be accessed at the bottom of this page. If you have any queries about the role, please contact Seirian Sumner at . If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact Biosciences staffing at . About you The successful candidate must hold an undergraduate degree in Bioinformatics, Computational Biology or other relevant subject area, and at least three years of experience working in the field beyond undergraduate level. The candidate will have proven excellence in handling and analysing genomic data and an excellent working knowledge of statistics. Experience of working with bioinformatics pipelines, and evidence of careful curation of bioinformatics code and workflows (e.g. via GitHub) is desirable. The successful candidate will have proven expertise in conducting comparative genomic analyses, including gene evolution (e.g. CAFÉ, PAML. HYPHY), gene synteny, gene regulation and exon structure across large datasets of chromosome-level genome sequences. The candidate will have experience in conducting phylogenetic analyses of trait evolution (e.g. MCMCGLMM), and an aptitude for the use of machine learning approaches (e.g. random forest) and have an interest in interpreting genomic d ata within an evolutionary framework.
Refer code: 3132113. Ucl - Biological Sciences - The previous day - 2024-04-03 10:30

Ucl - Biological Sciences

London, Greater London
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