School of the Built Environment and the School of Architecture
3 year, full-time funded PhD Studentship
Social Innovation in Low Carbon Transition: Bridging
the Gap between Energy Research and Social Sciences
Qualification Type: PhD
Location: Oxford
Funding for: UK Students, EU Students & International
Students
Funding amount: £15,009 per annum (with no inflation increase) for three years;
Fieldwork allowance: - £2,500 for 3 years
Hours: Full Time
Closes: 28 October 2019
Fees: Tuition fees up to Home/EU level
will be paid by the University Primary supervisor:Dr Esra KurulShort Introductory Paragraph
The School of the Built Environment and the School of Architecture are
jointly offering a 3-year full-time PhD Studentship. This inter-disciplinary
study cuts across the Smart Construction and Impact
Assessment and Low Carbon Building research groups,
which are part of the Oxford Institute for Sustainable
Development.
The studentship includes an annual bursary of £15,009 for three years (no annual increase) and fees
up to the Home/EU level. Any international student awarded the studentship
would need to cover the difference between international and Home/EU fees. Please
note, fees increase by 4% annually. The studentship has a start date of 20 January 2020. An April or September 2020 start may
also be possible. Full Project Detail
The key research question is:
How can the technological and digital literacies of
communities be developed/enhanced to set-up and operate renewable
energy systems that facilitate the move towards low carbon/smart
cities and communities?
The overarching goal is to
contribute to existing knowledge on urban social innovation in the field of
energy. Potentially using a mixed-method approach, the research will focus
on:
- existing social
innovation in the field of energy;
- energy
production, storage and consumption-related policies, and top-down and
bottom-up renewable energy systems and practices in leading ‘Smart/Low Carbon
Cities’;
- the relationships between smart
communities and the technological solutions to operating renewable energy systems; and
- the opportunities
for local communities to become equal partners in co-creating their urban
environments.
- The key output will be an
innovative framework to place prosumers at the heart of effective integration
of renewable systems in existing urban environments.
The successful candidate will be supervised by Dr Esra Kurul, Prof Rajat Gupta and Dr. Maurizio Sibilla. Entry requirements
We are looking for a highly competent and capable candidate to submit
his/her PhD thesis within 3 years. Candidates would be expected to have at
least an upper second class degree (or equivalent) and/or Masters in a related
subject (e.g. sociology, urban geography, architecture, planning, energy
studies, environmental studies, engineering, anthropology). They should
be able to demonstrate strong interdisciplinary research capabilities, be
fluent in spoken and written English.
The selection criteria will focus on academic excellence, suitability of
research experience/ skills, and subject knowledge. A demonstrable interest in social
innovation would be an advantage.
Contact details
Please contact Dr Kurul (ekurul@brookes.ac.uk) for informal enquiries.
How to apply
For further information on how to apply, please email tdestudentships@brookes.ac.uk for an application pack, quoting “Social innovation in low carbon transition”
in the subject line.
School of Engineering, Computing
& Mathematics
3
year, full-time funded PhD Studentship - Deep Learning for Modelling Complex
Video Activities
Eligibility: UK ,EU &
International candidates
Bursary: £16,000 per year (no annual inflation increase)
Fees: Tuition fees will be paid by the University
Deadline for applying: Friday 4 October 2019
Start date: January 2020
Primary supervisor: Professor
Fabio Cuzzolin
Short Introductory
Paragraph
The Faculty of Technology Design
and Environment at Oxford Brookes University is pleased to offer a three-year
full-time PhD studentship to a new student commencing January 2020. The successful candidate will work within the
Visual Artificial Intelligence Laboratory, under the supervision of Professor
Fabio Cuzzolin.
Full Project Detail
The Visual Artificial
Intelligence Laboratory is one of the top research groups in deep learning for
action detection. In 2017 we designed the first system able to localise
multiple actions in a video in real time. The Laboratory is running on a budget
of around £1.5 million, with six live funded projects, and is projected to
comprise 20/25 people in 2020. We closely collaborate with Oxford University,
Cambridge University, IIT Bombay, and others.
The successful candidate will contribute to
the research conducted under a new Research Agreement with Huawei Technologies
on “Deep learning for complex activity recognition”. The project aims to
explore new deep learning models of complex activities composed by multiple
events/actions, such as cooking a meal, or autonomous driving scenarios
involving, e.g., multiple vehicles negotiating an intersection.
The
successful candidate will be required to:
Develop new deep learning models for the detection of complex
video activities.
- Carry out their experimental validation.
- Collaborate with the other members of the Laboratory.
- Liaise with our industrial and academic partners
- Conduct literature searches and reviews, lead the preparation of
research papers for publication, and communicate results at conferences and
workshops.
Find out more
Please also consult the Lab’s web
site at http://cms.brookes.ac.uk/staff/FabioCuzzolin/.
Entry requirements:
The
essential selection criteria include:
A good first degree in Machine Learning, Computer Vision or
related fields.
- Experience in Machine Learning applied to Computer Vision.
- Good coding skills in Python, Matlab and/or C++.
- Ability to work independently or as part of a team.
- Excellent written and oral communication and organisational
skills.
The
desirable selection criteria include:
Experience and knowledge of deep learning techniques.
- Experience in action and activity recognition or video processing.
- Experience of coding in Torch, Tensorflow or Caffe.
- A track record of research publications in Computer Vision or
Machine Learning.
Contact details:
For all informal requests contact
Professor Fabio Cuzzolin (fabio.cuzzolin@brookes.ac.uk
How to apply:
To apply please request an
application pack by emailing: tdestudentships@brookes.ac.uk quoting “PhD Studentship in Deep Learning for
Modelling Complex Video Activities”.
As part of the application
process you must submit your CV, with a supporting statement (2-page maximum)
which explains why you believe you are the best candidate for this studentship.
School of Engineering, Computing and Mathematics
Low Carbon Vehicles Group
3.5 year full-time funded PhD Studentship
Eligibility: Home/EU and International
Students
Bursary: £16,000
per annum
A further £3,000 p.a. is
available to cover project costs
Fees: Tuition fees will be paid by the University.
Deadline: Monday 16th September
2019
Start date: January 2020 (Home/EU
students and International)
“Electric Powertrain Design and Optimisation/
Formula Student EV”
The Faculty of Technology Design and Environment at Oxford Brookes
University is pleased to offer a 3.5 year full-time PhD studentship to a new
student commencing in 2020. The
successful candidate, will work under the supervision of Prof Denise Morrey and
her team, and will also support the Oxford
Brookes Racing Formula Student Team.
For information about the Low Carbon Vehicles Group, see: /ecm/research/engineering/low-carbon-vehicles/
For information about the Oxford Brookes Racing Team, see:
https://obr.brookes.ac.uk/
The Formula Student Team has been very successful in the competition,
using an ICE based powertrain for two decades. The team now wishes to create an
advanced electric powertrain-based solution to align with the current trends in
Europe. This solution aims to utilise in-hub motors for a high performance four
wheel drive racing car.
The current electric powertrain relies on off the shelf motors and
inverters. This project aims to develop and improve motor inverter technology,
control, and HV architecture integration. The current motor inverters does not account
for interactions between sub-systems and, as a result, key attributes such as
efficiency do not reach the full potential available within the chosen envelope
of hardware and controls.
This project will develop and apply a new HV motor inverter design and
system architecture to maximise vehicle integration and efficiency. This
project also aims to develop improved modelling techniques and methodologies
for battery and motor modelling.
Requirements
We are looking to recruit a candidate of the highest quality who is
capable of submitting a PhD thesis within 3.5 years. Applicants would be expected to have a good relevant Engineering
degree. They should be able to demonstrate strong research capabilities and be
fluent in spoken and written English.
The selection criteria will focus on academic excellence, suitability of
research experience and skills, subject knowledge and references.
Application Process
If you would like to apply for this position, you should request an
application pack from the Research Support Office, tdestudentships@brookes.ac.uk, quoting “PhD
Studentship in Electric Powertrain”.
Fully completed applications must be sent to tdestudentships@brookes.ac.uk, by 5.00 pm on
Monday 16/09/19. As part of the application process you must submit your
CV, along with a supporting statement (2 page maximum) which explains why you
believe you are the best candidate for this role. Please be advised that the
selection process may involve an interview.
Information:
For all informal requests about the project and this post, please
contact Denise Morrey via email: dmorrey@brookes.ac.uk