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Duration of study:ÌýFull time - 4 years fixed term
Starting date:ÌýFlexible, available from December 2024
Application deadline:ÌýNo closing date, the position will remain open until a suitable candidate is found.

Primary Supervisor:ÌýDr Temitope Odedeyi, Senior Research Fellow, Department of Electronic & Electrical Engineering, University College London (ÂÒÂ×Ðã)

Project Description:ÌýThis project focuses on implementing Agri-Tech solutions for crop quality characterisation and to model and enhance crop yields focusing on cassava – a tropical root crop. The research aims to develop a robust machine-learning model for accurate crop yield prediction by integrating agronomic factors and data from strategically placed sensing stations across diverse agroecological zones. This model is targeted at empowering farmers to optimize resource allocation, manage pests and diseases, and adapt to climate change. Additionally, the study will create practical devices for non-destructive crop quality assessment, minimizing waste and enhancing marketability. The specific case study is cassava production in sub-Saharan Africa (SSA), although it is envisaged that the research output will be applied to other crops and in other contexts. Ultimately, the research aims to bridge technology gaps, promote innovative solutions, and contribute to sustainable agricultural development and food security in SSA and beyond.

We are offering a PhD position within the THRIVE (Agri-Tech for Sustainable Development: Crop Yield Prediction, Evaluation and Improvement) project. The research will be based within the ÂÒÂ×Ðã Institute of Communications and Connected Systems working on exciting multidisciplinary research on crop characterisation and yield modelling and optimisation. 

Funding:ÌýThis is a fully funded 4-year studentship to cover the Home student's tuition fees plus a £20,622/year stipend for living costs increasing with inflation as well as a top-up contribution towards travel and consumables. Although the fees are only covered at the Home rate, Overseas candidates are still welcome to apply. However, they would need to fund the difference between home and overseas fees themselves (e.g. through another award or self-funding) and specify this in their application.

More details about the stipend and fees can be found here: /research-innovation-services/award-services/research-studentships/studentship-budgets.

About the project: Crop Quality Characterisation

• Conducting a comprehensive review of the existing literature on the application of electrical impedance spectroscopy in crop characterisation.
• Theoretical modelling and experimental validation of the electrochemical properties of cassava roots as well as other root crops, exploring their response to RF (Radio Frequency) and microwave excitation.
• Application of equivalent circuit modelling to crop characterisation and modelling.
• Developing a look-up table that maps electrical impedance properties to quality metrics in cassava and other crops such as potatoes and carrots.
• Design and testing of prototype quality measurement devices and conducting lab and field testing of these prototypes 

Yield Modelling and optimisation

• Conducting a comprehensive review of the existing literature on crop modelling techniques.
• Aggregating and preparing environmental sensor data and historical data for crop yield modelling under different environmental conditions.
• Support the application of machine learning approaches to identify patterns in cassava yield from farm-level data and data captured from sensors already deployed in the field.
• Develop a cassava yield simulation model and calibrate it using the newly acquired data.
• Identification of the largest uncertainty factors in the yield model and improvement of model performance using artificial intelligence methods
• Support the development of climate change impact scenarios for cassava yield using the model.

The successful candidate will also contribute to the overarching goals of the research project team and publish the results in peer-reviewed scientific journals.

Qualifications required:ÌýCandidates should possess an upper second-class (or an overseas qualification of an equivalent standard) bachelor’s degree or above in Electrical Engineering or a related discipline. This is a highly interdisciplinary project and the ideal candidate would have experience in and passion for one or more of the following:

• Electronic circuit modelling and design
• Materials characterisation
• Machine learning

The following will constitute a distinct advantage:

• Competence in designing and conducting experiments, particularly in the areas of sensor development and testing. Experience with laboratory equipment and techniques for electrical measurements is preferred.
• Proficiency in programming languages such as MATLAB, Python, or similar for data analysis and modelling. Familiarity with simulation software for finite element modelling (e.g., COMSOL Multiphysics) would be beneficial.
• Experience or coursework in electrical impedance spectroscopy, theoretical modelling, experimental validation, and/or finite element modelling would be advantageous. Prior experience in agricultural research or crop science is desirable but not mandatory.
• Strong analytical and problem-solving skills to interpret experimental results, develop models, and derive meaningful conclusions from data.
• Excellent written and verbal communication skills are essential for presenting research findings, writing scientific papers for publication in peer-reviewed journals, and collaborating within a multidisciplinary team.
• Self-motivated with the ability to work independently, take initiative in research projects, and contribute creatively to problem-solving.
• Willingness to collaborate with team members, participate in group discussions, and contribute actively to the overall objectives of the research project.

The candidate should pass the entry requirements of PhD programme at ÂÒÂ×Ðã EEE: /prospective-students/graduate/research-degrees/electronic-and-electrical-engineering-mphil-phd

Working environment:ÌýWe offer a stimulating research environment within an interdisciplinary, collaborative team, with close partnerships with leading research organisations across Europe and Africa. The position is limited to 3 years, starting as soon as possible.

How to apply:ÌýFormal applications must be made using the ÂÒÂ×Ðã online application system by using the ÂÒÂ×Ðã postgraduate study application form. Please mark it to the attention of Dr Temitope Odedeyi.

To make informal enquiries, please contact Dr Temitope Odedeyi (t.odedeyi@ucl.ac.uk), provide a one-page statement outlining suitability for the project and a two-page CV (including contact details of two referees).

Equality, diversity, and inclusion:ÌýAs London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.

Applications from underrepresented backgrounds in engineering, such as women, ethnic minorities, or people with disabilities are strongly encouraged.

Contact:ÌýFor informal inquiries please contact Dr Temitope Odedeyi (t.odedeyi@ucl.ac.uk) who will be happy to answer any queries about the project.