409 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "inserm" Postdoctoral positions in United Kingdom
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. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the centre, collaborating across our
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opportunity to be part of an ambitious research programme developing new organoboron chemistry. The post is fixed term for 36 months, with a probationary period of one year. You will work in a collaborative and
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institutes working at the interface of technology and life sciences. This is a unique opportunity to contribute to a research programme that is technique-agnostic, impact-driven, and unafraid to push
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interview study. There is a strong expectation that the role holder will make significant contributions to the programming of experimental tasks and lead the technical set-up of the paradigms. Supported by
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Mental Health Younger Generations Programme. You will work with a friendly, supportive, passionate, and hard-working group to undertake statistical analysis of quantitative data to test hypothesis
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completion of, a relevant PhD/DPhil together with relevant experience. You will have the ability to lead and report an original research programme, as shown by a documented research track record, including
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to perform a broad array of bespoke tasks effectively and with minimum operator intervention. This role is an integral part of our EPSRC Programme Grant in Embodied Intelligence and will involve both
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-linear systems of ordinary differential equations and the proficient use statistical programming languages (R, Julia or Python), Bash computing and the development of computational packages are essential
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geography/remote sensing, ecology, statistics, engineering, quantitative social sciences, or a related discipline. Experience in developing models and mapping with real world data, with strong programming
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-world data, with strong programming proficiency in R or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven