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Nowadays the servers in data centres are so powerful that a single application would not be able to use all the resources of a server. Hence, multiple applications must be co-scheduled on the same machine. Since the applications compete for some of the resources, e.g. cache and memory, they will delay each other, which will affect system throughput, energy efficiency and revenues. Optimised scheduling strategies can minimise the financial loss and the environmental impact of data centres. The PhD candidate will research and develop new schedulers for data centres which make their decisions based on monitoring data using machine learning. The candidate will gain experience with scheduling techniques, machine learning, data centre hardware and monitoring tools. This project offers an exciting opportunity to push the boundaries of data centre scheduling. By developing new AI-enhanced schedulers for cloud computing and high-performance computing, the candidate will contribute to a fast growing market as the number of data centres is rapidly growing. The research will help with increasing their performance and reducing their carbon footprint. We seek candidates with excellent programming skills and a strong passion for machine learning and system optimisation. Knowledge in the following areas would be beneficial: high-performance and / or cloud computing, algorithms, problem solving skills, and experience in Linux or Unix.
Programme overview
Main Subject
Computer Science and Information Systems
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Nowadays the servers in data centres are so powerful that a single application would not be able to use all the resources of a server. Hence, multiple applications must be co-scheduled on the same machine. Since the applications compete for some of the resources, e.g. cache and memory, they will delay each other, which will affect system throughput, energy efficiency and revenues. Optimised scheduling strategies can minimise the financial loss and the environmental impact of data centres. The PhD candidate will research and develop new schedulers for data centres which make their decisions based on monitoring data using machine learning. The candidate will gain experience with scheduling techniques, machine learning, data centre hardware and monitoring tools. This project offers an exciting opportunity to push the boundaries of data centre scheduling. By developing new AI-enhanced schedulers for cloud computing and high-performance computing, the candidate will contribute to a fast growing market as the number of data centres is rapidly growing. The research will help with increasing their performance and reducing their carbon footprint. We seek candidates with excellent programming skills and a strong passion for machine learning and system optimisation. Knowledge in the following areas would be beneficial: high-performance and / or cloud computing, algorithms, problem solving skills, and experience in Linux or Unix.
Admission Requirements
3.2+
6.5+
92+
Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in a relevant subject. A relevant Master’s degree and/or experience is desirable.
31 Jan 2025
3 Years
Apr
Jul
Tuition fees
Domestic
4,786
International
27,500
Scholarships
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To help students navigate this challenging process, we recommend the following articles:
Application of Machine Learning for Job Scheduling in Computing Clouds PhD
Loughborough University, Loughborough, United Kingdom
# 251-300QS Subject Rankings
36 monthsProgramme duration
27,500 Tuition Fee/year
31 Jan, 2025Application Deadline
Programme overview
Main Subject
Computer Science and Information Systems
Degree
PhD
Study Level
PHD
Study Mode
On Campus
The PhD candidate will research and develop new schedulers for data centres which make their decisions based on monitoring data using machine learning. The candidate will gain experience with scheduling techniques, machine learning, data centre hardware and monitoring tools.
This project offers an exciting opportunity to push the boundaries of data centre scheduling. By developing new AI-enhanced schedulers for cloud computing and high-performance computing, the candidate will contribute to a fast growing market as the number of data centres is rapidly growing. The research will help with increasing their performance and reducing their carbon footprint.
We seek candidates with excellent programming skills and a strong passion for machine learning and system optimisation. Knowledge in the following areas would be beneficial: high-performance and / or cloud computing, algorithms, problem solving skills, and experience in Linux or Unix.
Programme overview
Main Subject
Computer Science and Information Systems
Degree
PhD
Study Level
PHD
Study Mode
On Campus
The PhD candidate will research and develop new schedulers for data centres which make their decisions based on monitoring data using machine learning. The candidate will gain experience with scheduling techniques, machine learning, data centre hardware and monitoring tools.
This project offers an exciting opportunity to push the boundaries of data centre scheduling. By developing new AI-enhanced schedulers for cloud computing and high-performance computing, the candidate will contribute to a fast growing market as the number of data centres is rapidly growing. The research will help with increasing their performance and reducing their carbon footprint.
We seek candidates with excellent programming skills and a strong passion for machine learning and system optimisation. Knowledge in the following areas would be beneficial: high-performance and / or cloud computing, algorithms, problem solving skills, and experience in Linux or Unix.
Admission Requirements
Tuition fees
Domestic
International
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
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Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
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Using the Metabolome to Study Aging and Geroprotectors in 3D Cell Models PhD
Visual Data Mining on Proteins and Biomedicine Crystallisation PhD
Waste-derived Bioplastics for a Circular and Sustainable Food Packaging Economy PhD
Life Sciences and Medicine (6)
Adaptive and Predictive Computational Modelling of Biomaterials: A Digital Twin Framework for Next-Generation Personalised Healthcare PhD
Adaptive and Predictive Computational Modelling of Biomaterials: A Digital Twin Framework for Next-Generation Personalised Healthcare PhD
Biomarkers of Aging PhD
Biomarkers of Aging PhD
Developing Prescription Guidelines for Passive Heat Therapy PhD
Developing Prescription Guidelines for Passive Heat Therapy PhD
Does Socialised Real-Life Body Exposure Promote Body Image Positivity PhD
Does Socialised Real-Life Body Exposure Promote Body Image Positivity PhD
Energy Dissipation In Human Soft Tissue During Impacts PhD
Energy Dissipation In Human Soft Tissue During Impacts PhD
Natural Sciences (6)
Accelerated Screening and Synthesis of New Chemotherapeutic Agents for Pancreatic Cancer PhD
Accelerated Screening and Synthesis of New Chemotherapeutic Agents for Pancreatic Cancer PhD
Bespoke Organometallic Compounds for Anticancer Studies PhD
Bespoke Organometallic Compounds for Anticancer Studies PhD
Bio-based Sustainable Materials for Autonomous Thermal Management in Wearables PhD
Bio-based Sustainable Materials for Autonomous Thermal Management in Wearables PhD
Biomimmetic Catalytic Asymmetric Synthesis of the Bisorbicillinoids and Related Products PhD
Biomimmetic Catalytic Asymmetric Synthesis of the Bisorbicillinoids and Related Products PhD
Climate and Ecological Transitions Hub Studentship PhD
Climate and Ecological Transitions Hub Studentship PhD
Coherent State Methods in Spectral Asymptotics PhD
Coherent State Methods in Spectral Asymptotics PhD
Computational Modelling of Sustainable Alloys PhD
Designing Classroom Tasks To Improve Students’ Learning Of Mathematics PhD
Developing Novel Antibiofilm Coatings for Sustainable Biofilm-Free Surfaces PhD
Development of Hybrid Microcomb Sources with Topologically Protected Dark Resonances for Simultaneous Classical and Quantum PhD
Development of Novel Bicyclopentanes (BCP) Bioisosteres From Bench Stable [1.1.1]-Propellane Precursors PhD
Digital Twins for Biofilm Management PhD
Dispersionless Integrable Systems In 2+1 Dimensions PhD
Social Sciences and Management (6)
An Evaluation of Erasmus+ Sport Projects and Their Impact on EU Sport Policy Development PhD
An Evaluation of Erasmus+ Sport Projects and Their Impact on EU Sport Policy Development PhD
Climate Change, Work Design and Worker Wellbeing Phd
Climate Change, Work Design and Worker Wellbeing Phd
Communication and Social Change (CSC) Hub Studentship PhD
Communication and Social Change (CSC) Hub Studentship PhD
Enhancing Motivation in Sport and Exercise Contexts PhD
Enhancing Motivation in Sport and Exercise Contexts PhD
Out of School Youth Provision: An Analysis of Funding and Operational Resilience within the Sector PhD
Out of School Youth Provision: An Analysis of Funding and Operational Resilience within the Sector PhD