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research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs
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upskill on algorithmic information theory, AIXI, Bayesian statistics, and reinforcement learning theory (existing expertise on these topics not required). Proven ability to independently design, build, and
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and objectives in various forums, national and international; and Act as line manager of the Centre Manager and the Knowledge Exchange Manager. Interested candidates are encouraged to contact the ICMS
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career objectives. To collaborate with other groups within GBI and with colleagues within the broader EIT family to deliver bold, ambitious and transformational research that would not be possible within