|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||£17,363 per year|
|Placed On:||23rd September 2022|
|Closes:||31st October 2022|
Eligibility: Home UK and international students
Bursary: £17,363 per year
Fees: Tuition fees will be paid by the university
Deadline: 31 Oct 2022
Start date: Jan 2023
With growing demand and popularity of cloud computing, hundreds of technology companies offer on-demand software and hardware services such as compute power, memory, disk storage, network bandwidth, email services, etc.. Such services are provisioned on negotiated agreement between service providers and consumers. However, given the vast diversity of services and quality criteria (e.g., security, reliability, performance), selection of appropriate cloud services has become one of the most challenging tasks for the cloud consumers. This research proposes a data science approach towards selection of cloud services. Data science is an interdisciplinary field that involves processing and analysing of large volume of data (big data) and requires expertise from different disciplines, mainly, computer science, mathematics and statistics.
How to apply
To apply for this studentship see the submission instructions on our website: https://sites.google.com/brookes.ac.uk/tde-research/studentships-how-to apply?authuser=0
When completing your application Online via
https://sites.google.com/brookes.ac.uk/tde-research/studentships-how-to apply?authuser=0 - please note the following: Title: A Data Science Approach to Cloud Services Selection
Please be advised that the selection process may involve an interview. Select the following course: MPhil/ PhD in Computing
Applications must be completed by 5pm GMT on Monday 31st October 2022
For informal inquiries about the project/application process contact Dr Muhammad Younas (firstname.lastname@example.org)
UK and international applicants can apply.
Applicants should have a first or upper second-class honours degree from a Higher Education Institution in Computing, Computer Science, Statistics or acceptable equivalent qualification.
Type / Role: