University of Edinburgh Centre for Doctoral Training in Machine Learning Systems PhD with Integrated Study دراسة The University of Edinburgh في

Centre for Doctoral Training in Machine Learning Systems PhD with Integrated Study

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Machine Learning (ML) has a great impact on our daily lives. Developments in ML are built on improved systems that can train and generate increasingly powerful models. Systems design greatly impacts ML performance and capability.Major advancements are made when ML and systems are developed and optimised together. This is relevant across many industries such as:in-car systemsmedical devicesmobile phonessensor networkscondition monitoring systemshigh-performance computingthe creative industriespatient caresocial networkinghigh-frequency tradingHowever, PhD training that combines systems and ML is rare, as research training is often separated into individual subdisciplines.Instead, we need researchers trained in both fields and experienced in working across them. This ML Systems PhD involves training collaborative researchers with experience across systems and ML.The programme is about machine learning that works to deliver for a need. It involves a holistic view of machine learning and systems that includes both a user-centric approach and an understanding of how to make things work.

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University of Edinburgh

خيارات الدراسة

دوام كامل (4 أعوام )

رسوم التسجيــل
£34,800.00 (US$ 44,942) سنوياً
هذه رسوم مؤقتة قيد القبول
تاريخ البدء

سبتمبر 2027

مكان عقــد الدورة

Main Campus

Old College, South Bridge,

Edinburgh,

EH8 9YL, Scotland, United Kingdom

دوام كامل (4 أعوام )

رسوم التسجيــل
£34,800.00 (US$ 44,942) سنوياً
هذه رسوم ثابتة
الموعد النهائي للتسجيل

متوقع December 2026

تاريخ البدء

سبتمبر 2026

مكان عقــد الدورة

Main Campus

Old College, South Bridge,

Edinburgh,

EH8 9YL, Scotland, United Kingdom

شروط القبول

للطلاب الدوليين

A UK 2:1 honours degree, or its international equivalent, in an area relevant to the CDT, for example, informatics, computer science, AI, cognitive science, mathematics, physics, engineering, or in another field with sufficient additional evidence of capability in the required areas.

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