PhD Studentships

PhD Funding

PhD Studentships

The University of Lincoln is making a significant investment to provide research opportunities for exceptional doctoral candidates through its annual half-million pound Research Investment Fund.

The quality and breadth of research at the University of Lincoln was highlighted in the Research Excellence Framework 2014, through which more than half of the University’s submitted research was rated as internationally excellent or world leading (3* or 4*). Lincoln was also placed in the top ten nationally for the quality of its research outputs in two major subject areas.

Studentships Terms and Conditions (MS Word)

Available Studentships

PhD Studentships in the College of Science

Applicants should have a first or higher upper second-class honours degree, and preferably a relevant Master’s degree (or equivalent experience) in Physical Geography, Earth Sciences, Environmental Sciences, and/or Life Sciences with substantial experience of qualitative research, excellent report-writing and English language communication skills and ability to work to deadlines.

Lincoln Centre for Autonomous Systems Research (L-CAS)

PhD Funded Studentship in Bioinspired Vision Systems For Automated Harvesting (funded by AHDB)

This AHDB funded PhD will investigate the crucial problem of rapidly and robustly segmenting fruits and flowers from background vegetation which is considered key component to automation of labour-intensive horticultural processes such as fruit and flower harvesting.  Inspiration will be taken from the vision system of insects that solve exactly this issue (e.g. bees, fruit-flies, aphids) with the aim to develop novel hardware and software solutions based on key abstractions. The selected candidate will benefit strongly from working in close collaboration with researchers at the University of Lincoln’s Institute for Agri-Food Technology & Centre for Autonomous Systems and with horticultural industrial partners ensuring tight coupling of academic output with commercial application. 

You should have a good Bachelors or Masters in Computer Science, Electronic Engineering, Mathematics or Physics. You must have excellent mathematical, and experience in related areas such as optics, machine learning, computer vision software and hardware development are all considered beneficial. 

Read more (MS Word) 

Stipend/Living allowance: £14,296 per annum
Start date 1st October 2017 (exact start date may be negotiable)
Duration: 36 months
Reference: AMS 915466

In the first instance, please contact Dr Mike Mangan (, with your CV and transcript.  Please put "AHDB Biovision PhD application" in the subject line. Applications will be assessed as they arrive and, if appropriate, we will contact applicants to discuss things further. 

School of Computer Science

PhD Funded Studentship in “Deep Neural Networks, Adaptation and Transparency”

Over the past 5 years significant growth has occurred in technologies that relate to machine learning & understanding, knowledge modelling & management, data science. Machine Learning, a branch of Artificial & Computational Intelligence, focuses on designing, developing and studying the algorithms that learn from data. Models of learning try to follow the function of the human brain, creating machines with intelligent behavior, which are able to reason, predict and adapt to changing environments, assisting humans in their activities & interactions.

The research interests of the mlearn group cover a variety of subfields where machine learning meets data science, intelligent systems, knowledge representation and reasoning, multimedia and multimodal content analysis, indexing and retrieval, semantic metadata interoperability and search, behavior recognition and affective interactions, sentiment analysis, as well as applications in medical data analysis and health care monitoring, cultural content search and digital libraries, computational finance, computational advertising, smart homes, smart cities and Internet of Things.

The successful candidate will investigate the area of deep neural networks and deep learning for signal and/or big data analysis, especially related to adaptation and transparency issues in applications, such as healthcare and complex data processing. The candidate will benefit strongly from the collaborations we have both within the University of Lincoln and internationally.

Applicants should have a good honours Bachelors or Master’s degree in Computer Science, Engineering, Mathematics or Physics. Applicants must have an excellent mathematical background. Experience in related areas such as machine learning, deep learning and computer vision as these areas are considered beneficial.  

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Open to UK and EU Students only
Stipend/Living allowance: £14,000 per annum
Start date 2 October 2017 (exact start date may be negotiable)
Duration: 36 months
Reference: COS-SOCS-2017-1

Informal enquiries may be made to Professor Stefanos Kollias ( or alternatively Dr Georgios Leontidis (

To apply, an application of a CV, degree transcripts, and a 1-page covering letter including a brief insight into the research topic area should be emailed to Professor Stefanos Kollias and Dr Georgios Leontidis Applications must state “PhD application – Deep Neural Networks” in the subject line.  

Applications will be assessed on arrival. Should further information be required the applicant will be contacted.  The position will remain open until filled.