Fully-funded PhD positions and post-docs
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21/05/2023: We have two job openings as Research Assistant or Associate in Scientific Machine Learning (2 posts) (Closing date: 2nd June 2023) https://www.imperial.ac.uk/jobs/description/ENG02625/research-assistant-associate-scientific-machine-learning under the UKRI AI for Net Zero grant "Real-time digital optimisation and decision making for energy and transport systems". If you are interested, please apply through the official portal via the link above. Applications made via other channels (for example email) will not be considered.
Applicants for a PhD should have a strong academic track record (a first-class, or equivalent) in a scientific, mathematical, or engineering discipline. Background in computational physics / mathematics and scientific computing are an advantage. Applicants for a post-doc should have a PhD in a scientific, mathematical, or engineering discipline with a publication record. Some experience of scientific computing is essential. Current funding (UKRI AI for Net Zero): Real-time digital optimisation and decision making for energy and transport systems EP/Y005619/1. Current funding (UKRI New Horizon): Can quantum algorithms revolutionise the simulation of turbulent flows? https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/X017249/1 Current funding (ERC Starting Grant): Physics-constrained adaptive learning for multi-physics optimization https://cordis.europa.eu/project/id/949388 Current funding (UKRI ExCalibur): Turbulence at the exascale: application to wind energy, green aviation, air quality and net-zero combustion Exascale Computing Grants |
Past fully funded positions
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1/11/2022. One fully-funded postdoctoral position in Quantum algorithms for the simulation of turbulent flows.
1/6/2022. One fully-funded PhD studentship in Physics-aware machine learning for multi-physics flows. 04/2022. Fully-funded post-doc position in "Physics-aware machine learning for exascale fluid mechanics" funded by UKRI/EPSRC 01/2022. Fully funded post-doc in "Research Associate in machine learning for multi-phase flows", funding from EPSRC, Programme Grant PREMIERE 09/2021. Fully funded PhD studentship "Research Assistant in Physics-aware machine learning", funding from (ERC) starting grant, PhyCo project. 09/2021. Fully funded PhD studentship "Research Assistant in Physics-aware data assimilation", funding from (ERC) starting grant, PhyCo project. 09/2021. Fully funded post-doc position in Physics-aware of machine learning for flow optimization, funding from (ERC) starting grant, PhyCo project. 09/2021. Fully funded PhD studentship “Physics-aware machine learning for complex flows”, funding from EPSRC 09/2021. Fully funded PhD studentship “Physics-aware machine learning for flow reconstruction”, funding from EPSRC 04/2021. Fully funded EPSRC-DTP PhD studentship in "Physics-aware machine learning for turbulence". 10/2020. Fully funded EPSRC-DTP PhD studentship in "Data assimilation in fluids". 03/2019. Fully funded EPSRC-DTP PhD studentship in "Prediction and control of extreme fluid dynamics with artificial intelligence". 05/2018. Fully funded post-doctoral position sponsored by the Hans Fischer fellowship on "Artificial intelligence algorithms in computational fluid dynamics". |