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PhD Studentship in UAV-Aided Smart Data Collection and Processing for Wireless Sensor Networks using Machine-Learning Techniques

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  • Full or part time
    Dr E Nurellari
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Qualification type: PhD

Location: Lincoln

Funding for: UK Students, EU Students, International Students

Funding amount: Home/EU tuition fees and a stipend of £15,000 per annum for a duration of 3 years and 6 months

Hours: Full Time

Closes: 30th March 2020

Start date: 1st June 2020

Duration: 3 years and 6 months

Number of studentships: 1

The Lincoln School of Engineering was the first wholly new engineering School to be opened in the UK for decades, with investment from HEFCE, the European Regional Development Fund and Lincolnshire County Council. At the forefront of the School’s objectives is to support leading-edge research of the highest quality and to provide a sustainable research environment as a global centre of excellence in the Industrial Energy and Systems engineering sectors.

This is a call for applications for a fully funded PhD studentship at the School of Engineering, University of Lincoln, in ‘UAV-Aided Smart Data Collection and Processing for Wireless Sensor Networks using Machine-Learning Techniques’. You will be part of the Communication, Networks, and Embedded Systems (CNES) research group within School of Engineering. Most of the research activities within CNES are externally funded (approx. £2 million portfolio). This is a unique and exciting opportunity to further a career in Internet of Things and WSNs. CNES team includes both academics and industrial experts, and team-working is an important part of this project.

The research will demonstrate how Internet of Things and emerging digital technologies enable low cost continuous data collection and without the need for onsite instrument and data specialists. Specifically, this research study has the following objectives:

• Design and implement practical WSN demonstrators and embed Machine Learning techniques to perform data analysis
• Develop the sensing (measuring) module, communication module and statistical prediction model. Combine all the selected off the shelf sensors (e.g., the temperature, pH, wind sensors, etc.) and connect to the cloud.
• Develop algorithms within the cloud to predict undesired Region of Interest (ROI) condition. Develop the user interface (pc or/and smartphone).
• Evaluation of developed technologies and methodologies.

As part of the Studentship you will also be expected to deliver a maximum of six hours per week of teaching support if and when required.

Eligibility criteria

Open to all students of any nationality without restrictions (UK/EU and International)

For international students only (non-EU): This funding will cover tuition fees for UK/EU students only. To study at University of Lincoln, you must hold a valid visa which entitles you to study at the University.

Academic criteria

Candidates should possess a Honours degree (1st, 2.1 or equivalent), and/or Masters degree in the area of Electrical/Electronics, Computer Science and Engineering, Robotics, Embedded Systems, Mechatronics or related fields, and are interested in the topics, including modelling and designing Wireless Sensor Networks, some experience of programming in C/C++ or embedded platforms/related design tools., data processing and visualization, data mining and intelligent systems, etc.

English language requirements

Applicants whose first language is not English are normally expected to meet the minimum University requirements (e.g. 6.5 IELTS).

Informal enquiries can be made by e-mail to Dr. Edmond Nurellari: [Email Address Removed]

To apply please email a research proposal, CV, highest qualification certificate/transcript and two reference letters to: [Email Address Removed] quoting the following reference: ENGWSN001

The closing date for applications is 30th March 2020. However, applications will be accepted till the position is filled.

Interviews for shortlisted candidates are expected to take place during April 2020, with a start date in June 2020.

Funding Notes

Full UK/EU/ tuition fees + £15,000 per annum stipend + other benefits

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