PhD Studentships

We are pleased to announce three full-time PhD research posts in the areas of the Internet of Things/wireless sensing and data science based at Cogent Labs, Coventry University (Coventry, UK).

Cogent Labs is a world-leading applied research group at Coventry University, dedicated to analysis and development of sensing-based sociotechnical systems. It has a dual focus: robust, deployable pervasive sensing systems for real-life applications at scale; and effective packages for empowering users to maximise the benefits of those systems.

The successful candidates will work within the EPSRC HELP-Refugee project, researching into understanding energy needs and providing new technical solutions for displaced populations in Rwanda and Nepal. With a particular focus on Energy – one of the 17 Global Goals for Sustainable Development. You will work with an interdisciplinary team of scientists, and your work will be supported by a number of project collaborators (Practical Action, NGO and Scene – a social IT enterprise pioneering solutions in the energy sector).

During the project, you will need to undertake some field work, as well as taking up challenges that naturally come with interdisciplinary work that crosses the engineering and computer sciences domains. Throughout the project, you will develop as a researcher, scientist and individual, through a structured learning programme that encourages you to use your strengths while gaining new skills. You will provide theoretical contributions to the field and have the opportunity to evaluate your work in real-life scenarios offered by the HELP-Refugee project.

KEY DETAILS

  • Eligibility: UK/EU/International students with the required entry requirement
  • Award Details: £15000 bursary plus tuition fees
  • Duration: Full Time – between 3 years and 3 years 6 months fixed term
  • Application deadline: 30th June
  • Interview dates: TBC
  • Start date: September 2018
  • Informal enquiries are essential before application; contact Professor Elena Gaura to discuss this opportunity.

THE PROJECTS

LONG-LIVED NETWORKED SENSORS IN REAL-LIFE DEPLOYMENT

Reducing energy consumption of wireless sensor nodes extends battery life and/or enables the use of energy harvesting and thus makes feasible many applications that might otherwise be impossible, too costly or require constant maintenance. The area of low-power long-lived sensor-based systems has seen many developments recently – from scientists and practitioners alike. Over the past few years, we have also witnessed a proliferation of sensor network deployments that provide a sound base for studying network longevity and the development of solutions to address component failures.

This project will focus on investigating sensors and server failure modes in wireless networked sensor systems. You will develop both theoretical and practical solutions for preserving network life. These solutions will account for the application level data needs and the viability of the deployed network as an informational decision-enabling tool in specific real-life settings.

Depending on your background, the project will have a variable weight on theoretical and/or practical contributions to the field. The successful candidate will work with a variety of sensor networks that will be deployed for monitoring energy interventions (from mobile lanterns to micro-grids) in multiple international locations. This will offer real-life deployment data and the opportunity to test solutions for long-lived sensor network concepts that you will develop through your research.

Expected candidate skills:

  • Strong and proven programming skills—essential
  • Understanding of wireless network protocols and principles – essential
  • Demonstrable experience with embedded/wireless systems programming—essential
  • Working knowledge of electronic systems design/implementation—desirable
  • Working knowledge of machine learning—desirable
  • Demonstrable experience with data analysis and data processing principles and tools—desirable.

For more information or to apply see: https://www.coventry.ac.uk/research/research-students/research-studentships/long-lived-networked-sensors-in-real-life-deployments/

DATA MINING FOR MIXED METHODS ENERGY DATA SETS – DEALING WITH UNCERTAINTY AND CALIBRATING THE “HUMAN SENSOR”

The project will look at the challenges and opportunities of inferring knowledge from and/or making decisions based on diverse datasets such as those obtained from energy systems and questionnaires.

There is a wide availability of low-cost wireless networkable sensors that can gather data about environments, human behaviours and interactions between people and common life objects. Dedicated networks can be built to collect detailed data over long periods of time. However, much of our understanding about human behaviour has come from surveys, interviews, focus groups and ethnographic studies. New methodologies that correctly analyse diverse, mixed datasets (sensor based and survey-based) are critical to enhance our understanding of human behaviour, needs and aspirations, and drive decisions in response to a number of development challenges.

You will have access to energy survey data collected by the HELP-Refugee project team as well as data streamed from hundreds of wireless sensors embedded in deployed energy interventions (such as mobile lanterns, cookstoves, street lights and microgrids).

Expected candidate skills:

  • Relevant degree in Mathematics, Computer Science disciplines or Social sciences
  • A desire and ability to work across disciplines and in an interdisciplinary subject area focusing on data and mixed research methodologies – essential
  • Programming skills in a language/tool of choice—essential
  • Strong Mathematics or Statistics background—essential
  • Demonstrable experience with data analysis and data processing principles and tools—essential
  • The desire to participate in fieldwork—essential
  • Working knowledge of machine learning tools and techniques —desirable.

For more information or to apply see: https://www.coventry.ac.uk/research/research-students/research-studentships/data-mining-for-mixed-methods-energy-data-sets-dealing-with-uncertainty-and-calibrating-the-human-sensor/

DEMAND MANAGEMENT AND ADAPTIVE USER-DRIVEN ENERGY DISTRIBUTION IN RENEWABLE MICRO-GRIDS

Micro-grids augment the traditional approach of national electricity grids with local power generation and control; this potentially lowers costs and transmission losses. Some of the problems faced by communities when implementing micro-grids are to do with a lack of accessible tools for management and control. Management is needed to account for context-dependent energy needs in a community served by a micro-grid. Control is required to allow non-essential systems to be powered when supply exceeds essential demands and essential systems need to benefit from power-up in critical situations.

The aims of the proposed PhD programme are to inform the development of wireless devices and tools to support integrated community-based micro-grids and micro-generation /distribution control; and map the current gaps in education and technology that make them inaccessible or difficult to apply in the context of displaced populations and refugee camps. The project will include the development of prototype micro-grid management and control systems—based around wireless sensing and actuation—which are fit for purpose in functional deployed micro-grids.

Expected candidate skills:

  • A relevant degree in Computer Science, Electronics, Engineering or similar
  • Strong and proven programming skills—essential
  • Experience in one or more of the following areas is highly desirable: embedded systems, wireless sensor networks, energy systems modelling, micro-grids, control, and electronics
  • Ability to work with real-life hardware systems and a desire to understand necessary fundamentals of distributed energy systems, renewables and mechanics/control
  • A desire to work in the field, and internationally.

For more information or to apply see:  https://www.coventry.ac.uk/research/research-students/research-studentships/demand-management-and-adaptive-user-driven-energy-distribution-in-renewable-micro-grids/

FUNDING

  • £15,000 bursary plus tuition fees  – UK/EU/International
  • For the academic year 2018/19, any English student who is not part of a research council can borrow up to £25,000 to help cover the cost of their PhD tuition fees. Further details can be found here.

THE UNIVERSITY

Coventry University has been voted ‘Modern University of the Year’ three times running by The Times/Sunday Times Good University Guide. Ranked in the UK’s top 15 (Guardian University Guide), we have a global reputation for high-quality teaching and research with impact. Almost two-thirds (61%) of our research was judged ‘world leading’ or ‘internationally excellent’ in the Research Excellence Framework (REF) 2014. By joining the University’s Faculty of Engineering, Environment and Computing (EEC), you will benefit from state-of-the-art facilities and partnerships with relevant industry and other third parties.

BENEFITS

  • Our research strategy is underpinned by a £250m investment in research and facilities
  • Dedicated Doctoral College and Centre for Research Capability Development delivers high-quality professional support for researchers, from PhD to Professor
  • Free training: research career planning, managing your doctorate, research communication skills, research ethics, research impact, research integrity, research methods and research supervision
  • Coventry is a member of the Doctoral Training Alliance (DTA), the largest multi-partner and only nationwide doctoral training initiative of its kind.

ENTRY REQUIREMENTS

Successful applicants will have:

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average.
  • In the event of a first degree classification of less than 2:1, a Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at minimum merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at minimum merit level (60%), plus
  • the potential to engage in innovative research and to complete the PhD within a three-year period of study
  • a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

The research leading to these results has received funding from the EPSRC Global Challenges Research Fund under grant agreement n° EP/P029531/1.
| The research presented in this website has undergone ethical approval at Coventry University reference: P61091.