Research Studentships

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Funding Your Research

At the University of Lincoln, postgraduate students are an integral part of our research community. They work alongside talented academics and researchers from around the world, contributing to our growing reputation for internationally excellent research.

There are opportunites to get involved in exciting research projects by applying for a studentship. The University offers a range of studentships including funded and part-funded opportunities, please refer to the current studentships information below.  

CDT 2 Col

EPSRC Centre for Doctoral Training

The University of Lincoln is launching the world's first Centre for Doctoral Training in Agri-Food Robotics in collaboration with the University of Cambridge and the University of East Anglia. This new advanced training centre in agri-food robotics will create the largest ever cohort of Robotics and Autonomous Systems (RAS) specialists for the global food and farming sectors, thanks to a multi-million pound funding award the Engineering and Physical Sciences Research Council (EPSRC).

Applications are now open for entry into the CDT programme, starting in September 2020.

Find out More

Current Studentship Opportunities

Use the dropdown menus below to browse current funded and part-funded studentship opportunities at the University of Lincoln, listed by academic College. 

Studentship Terms and Conditions

College of Science

Accurate Control of a Low-Cost Soft Robotic Arm for Automated Strawberry Picking

Supervisors: Khaled Elgeneidy (University of Lincoln), Dr Charles Whitfield (NIAB EMR).

Reference: CTP_FCR_2020_5

The UK alone produces 120,000 tons of strawberries a year (British Summer Fruit Association, 2017) and yet is only the 13th largest producer of strawberries in the world against 3 million tons produced globally. The harvesting of this significant strawberry production is currently heavily labour-intensive, employing over 29,000 seasonal fruit pickers, who are becoming increasingly difficult to recruit due to the unattractive nature of the job, low wages, and seasonal demand. Recognising the challenges in recruiting sufficient human pickers, the industry is under significant pressure to consider automating the harvesting of strawberries via novel robotic solutions.

Objective and Approaches

The successful PhD candidate will work on the development and control of a bespoke soft robotic arm for strawberry picking. The objective is to provide a low-cost flexible manipulator that can be deployed on a fleet of robots to address the current challenge in harvesting strawberries due to labour shortage. The soft arm should enable reaching strawberries through clutter with the required grasping pose and delivering of picked strawberries by utilising the soft arm’s morphology. The work will consider online learning control methods to account for material nonlinearities and unknown external forces, in order to improve the positioning accuracy during dynamic interaction with the environment. This is expected to involve embedding flexible sensors to provide the necessary sensory feedback.

The successful candidate will join a large team of researchers developing robotic solutions to address the global challenges facing crop-based agriculture. The University of Lincoln is home to Lincoln Agri-Robotics (LAR), the world’s first global centre of excellence in agricultural robotics, as well as the Lincoln Centre for Autonomous Systems (L-CAS). The University is also the lead institution for the new EPSRC Centre for Doctoral Training in Agri-Food Robotics (AgriFoRwArdS), together with partners at the University of Cambridge and University of East Anglia.

Researchers at the University of Lincoln can benefit from excellent facilities and equipment, such as the Franka arms and a fleet of Thorvald mobile robots, as well as strong links to an extensive network of industry partners across the agri-food chain. Additionally, the university’s 200-hectare Riseholme Campus, hosts a robotic fruit farm, including strawberry polytunnels for testing robots in a realistic environment. 

The sucessful applicant will be registered with the University of Lincoln. Beginning in October 2020, the candidate should have (or expect to have) an Honours Degree (or equivalent) with a minimum of 2:1, in Mechanical Engineering, Robotics, Mechatronics, or a related subject. 

Application, Eligibility, and Funding

For more information regarding eligibility and funding, and to request an application form, potential applicants should contact recruitmentctp@emr.ac.uk citing the reference. The deadline for applications is 28 February 2020.

Contact Dr Khaled Elgeneidy (kelgeneidy@lincoln.ac.uk) for an informal discussion.

Further Details

http://www.ctp-fcr.org/robotic-arm/

 

Precision Agriculture: AI- and Expert-Based Approach to Forecast Fruit Production in High Intra-Field Variation Settings

Supervisors: Professor Stefanos Kollias (University of Lincoln), Dr Georgios Leontidis, University of Lincoln/University of Aberdeen, David May (University of Lincoln), Dr Mark Else (NIAB EMR).

Reference: CTP_FCR_2020_12

In soft fruit industry, farmers are required to provide the retailers with accurate numbers of their produce to make sure the market demand is being met. Failing to accurately do so can lead to a) underestimating production, hence having to waste their produce adding to food waste and increasing the carbon footprint, or b) overestimating production, hence not meeting the expectations of the retailer leading to hefty penalties or damage to their reputation. Providing accurate yield forecasting has long been the target of the fruit industry, which still suffers from high errors, due to the various uncertainties that forecasting entails, such as weather and seasonal variations.

Another problem many farmers often face is intra-field fruit crop variation, i.e. specific areas of the farm performing worse than others. Modern farms and greenhouses collect various types of data for monitoring purposes. However, with the outburst of big-data analytics and Machine Learning this information can be used to develop algorithms and models that can be useful and inexpensive tools to the farmers. Given the highly competitive nature of the sector, farmers need tools not only for monitoring the field performance but also for providing them with insights such as accurate yield predictions. Currently, farmers rely on experience-based/empirical predictions, which sometimes do not represent the reality due to factors/patterns they fail to consider. That means they might provide wrong estimates to the retailers, leading to either wasting produce or missing to meet the demand. 

Objectives and Approaches

This project aims to develop novel Machine/Deep Learning methodologies and Bayesian techniques to forecast fruit production and quantify uncertainty under settings that include high intra-field variations. The project consists of the following key activities:

- Forecasting yield from time-series and numerical data via developing novel deep learning techniques revolving around the use of recurrent and transformer networks. Our approach will be to collate and incorporate data pertaining to the growth of the plant as well as various environmental parameters. Our implementations will focus on developing Deep Transformer and Recurrent Kalman Networks with self-attention to identify properties of the data that incorporate the most useful information and will be optimised through Generative Adversarial Networks.

- Incorporating expert knowledge to the data-driven model for improving the forecasting process. In application domains such as agriculture data do not come in abundance. Therefore, we aim at liaising with experts, such as growers, to also add physical constraints to our data-driven models.

- Developing self-supervised learning techniques to enhance the learning process and implement robust and generalisable techniques. This will be achieved through the use of pretext tasks, such as data imputation, to enhance the representation learning not having to rely only upon the yield information but instead try to exploit interdependencies in the raw data that can assist with the task at hand. To do so we will create a loss function that will encompass the pretext task and couple it with the loss function of the task of interest, i.e. yield forecasting, to be used during the training phase.

- Conducting intra-field variation through the use of datasets that include information of the yield across different parts of the field. Causal analysis will be performed to identify factors that might contribute to this variation and will also be combined with deep learning techniques and Monte Carlo dropout to obtain uncertainty estimates for each part of the field. The uncertainty estimate will accompany the yield forecasting for the different parts of the field.

The successful applicant will be registered with the University of Lincoln. We are looking for a highly skilled PhD student with a background in computer science/engineering and a strong interest in machine learning in agriculture. The studentship will provide advanced training in novel machine/deep learning techniques and the opportunity to work closely with crop physiologists and growers.

Application, Eligibility, and Funding

For more information regarding eligibility and funding, and to request an application form, potential applicants should contact recruitmentctp@emr.ac.uk citing the reference. The deadline for applications is 28 February 2020.

Contact Professor Stefanos Kollias (skollias@lincoln.ac.uk) for an informal discussion. 

Further Details

http://www.ctp-fcr.org/ai-expert/

 

Lincoln Agri-Robotics PhD Studentships

 

Fully-funded three-year PhD studentships are available within Lincoln Agri-Robotics (LAR), the world's first global centre of excellence in agricultural robotics, recently funded by UKRI's Research England. The Centre bridges and expands the strong collaborations that exist between two leading research groups at the University of Lincoln: the Lincoln Institute for Agri-Food Technology (LIAT) and the Lincoln Centre for Autonomous Systems (L-CAS). Students have the opportunity to work on projects that strive to make a real difference in the world, by investigating challenges that face the global agri-food industry: climate change, population growth, political pressures affecting migration, and ageing populations.

There are 6 studentships available. Students will focus their research within one of three grand challenges prioritised by LAR, while developing their own skills and knowledge as roboticists. These challenges are: (1) selective harvesting, e.g. picking a strawberry; (2) crop care, e.g. use of robotics to monitor crops, soils and environment; and (3) phenotyping robotics, e.g. using robotics to gather data and make decisions on plant traits, weeds, pests, and disease.

The key technologies targeted for PhD research contributions lie in one (or more) of the five specialties essential to LAR (mobile autonomy, manipulation and soft robotics, sensing and perception, fleet management, and human-robot collaboration). Students can gain experience developing research strategies, implementing approaches on physical robots, testing solutions in live fields, and/or evaluating systems with end users.

Our fully-funded studentship package includes:

  • All PhD tuition fees paid
  • tax-free stipend at UKRI rates to cover living costs
  • A Research Training Support Grant (RTSG)
  • Additional funding to support outreach and dissemination, attendance at summer schools, research events, and development projects.

Students can also benefit from:

  • The opportunity to develop their career, working alongside and in collaboration with academic and industry specialists of the future.
  • Internships, project work, and engagement opportunities with world-leading companies who are interested in both research collaboration and future postdoctoral graduates.
  • LAR PhD students will have the opportunity to study alongside students in the EPSRC Centre for Doctoral Training in Agri-Food Robotics (AgriFoRwArdS), led by the University of Lincoln in collaboration with thr universities of Cambridge and East Anglia.

Applications

We are looking for dynamic, focused graduates with a first or upper second-class honours degree, a Master’s degree, or equivalent professional experience.

PhD Studentships Application Form

The current round of applications closes on 22 March 2020. Places are limited so early application is advised. 

Apply by sending the following documents to the LAR team at lar@lincoln.ac.uk.

- Completed Application Form

- Current CV

- Transcript of your first degree

- Transcript(s) of any previous degrees

 

For further enquiries, please contact the LAR team at lar@lincoln.ac.uk.

Recovery of Metals/raw Materials from Wastes, Residues, and Ashes Produced Through the Thermochemical Conversion of Phytomined Biomass

PhD Fee Waiver Scholarship

Reference Number: ENG008

Project Leads: Dr Jose Gonzalez-Rodriguez, Dr Abby Samson

Overview

Heavy metal contaminated land covers a large expanse throughout Europe and is often considered unsuitable for agriculture. Certain biomass crops have been identified as capable of phytoremediating such land (including Miscanthus).

This presents great opportunities in terms of land utilisation and remediation, but also poses interesting challenges with the production of a now contaminated biomass fuel. The heavy metal uptake of this fuel makes it unsuitable for traditional thermochemical use. There is also an excellent opportunity to recover metals and raw materials from this fuel, which would aid in the EU’s challenge of finding new sources of raw materials and also render this contaminated fuel usable once again.

This PhD project will focus on the following issues:

  • Metal uptake by biomass from contaminated land (efficacy of uptake, determination of which metals are absorbed, metal concentrations and partitioning within the plant).
  • Partitioning and fate of metals within waste streams from typical thermochemical conversion routes (pyrolysis, combustion and gasification). 
  • Development of novel methods for metal recovery from untreated fuels as well as from each of the waste streams through the use of molecularly imprinted polymers.
  • Development of online sensors to aid in the detection of the metals in the different treatment streams.

Funding Package

The scholarship covers tuition fees for the PhD up to the value of the UK/EU fee level. Overseas students may apply and the student will be responsible for the difference between the UK/EU, and overseas fee level. The grant holder will also be exempt from paying bench fees.

As living costs are not covered by this award, it is assumed that the grant holder will be applying for a PhD loan from the government (£25,000) for the three years research in order to guarantee a steady income to support themselves during their studies. However, candidates may secure other funds to pay for their living and maintenance during their PhD.

Contact: 

For informal enquiries, please contact Dr Jose Gonzalez-Rodriguez (jgonzalezrodriguez@lincoln.ac.uk) or Dr Abby Samson (asamson@lincoln.ac.uk) for further information and to discuss details of the application.

Entry requirements

Applicants should have an appropriate Master’s degree. Suitably qualified candidates worldwide may apply, although International students must self-fund the difference between the International and UK/EU fee rate. 

Apply Now

Details

Applications are open until the vacancy is filled.

Open for UK, EU, and Overseas Students.

Tuition Fees included (capped at UK/EU level).

Living expenses are not included.

 

College of Social Science

Plastics Pollution, International Environmental Law, and Earth System Governance

PhD Funded Studentship

Reference Number: LAW2020-1

Project Leads: Professor Elizabeth Kirk ekirk@lincoln.ac.uk

Overview

The problems posed by plastics pollution are becoming increasingly obvious to all. At the same time efforts to curb that pollution appear somewhat faltering in nature. Our understanding of the ability of international law to tackle plastics pollution is also somewhat limited. Actions may be taken under a variety of treaties such as the Basel Convention, but questions arise as to how actions to curb pollution interact with provisions under other, seemingly unrelated, regimes such as those governed by the World Trade Organisation. Addressing these questions requires connections to be made between international law and the Earth System Governance agenda. This studentship is focused on these interactions and on the potential pathways to successful/effective regulation of plastics that may be provided through Earth Systems Governance.

Contact: Professor Elizabeth Kirk ekirk@lincoln.ac.uk

How to Apply

Applicants should have a first or upper second class honours degree or equivalent in a relevant area. Applicants with a relevant Master's degree are particularly welcome. Applicants should possess excellent academic writing and English language communication skills and an ability to work to deadlines.

Apply Now

Those called for interview will be required to prepare a presentation.

Closing Date: 10 March 2020

Interview date: provisionally week beginning 23 March 2020

Start date: 1 September 2020

Eligibility and Funding

The studentship covers the cost of UK/EU fees and an annual stipend of £15009 (subject to revision in line with the UKRI PhD stipend rates) for a maximum of 3 years.

Suitably qualified candidates worldwide may apply, although international students must self-fund the difference between the International and UK/EU fee rate.

 

Improving Prehospital Care for Chronic Respiratory Disorders

PhD Funded Studentship

Reference Number: HSC2019-4

Supervision team: Professor Niro Siriwardena, Professor Graham Law, Dr Arwel Jones.

Overview

Applications are invited for a fully funded studentship associated with the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (NIHR-ARC East Midlands) East Midlands. Students can join a thriving research environment based at the Community and Health Research Unit and Lincoln Institute for Health at the University of Lincoln. Candidates are sought with interests in prehospital ambulance care of chronic respiratory disorders using statistical analysis of large datasets combined with qualitative methods.

The successful candidate will join an active and growing research centre, the Community and Health Research Unit (CaHRU) at the University of Lincoln and the Lincoln Institute for Health (LIH), working on prehospital and primary care quality and outcomes research.

Experience in scientific research in relation to health will be desirable but not essential. Strong scientific qualities will be essential.

Contact: Professor Niro Siriwardena at nsiriwardena@lincoln.ac.uk or Dr Arwel Jones at ArJones@lincoln.ac.uk

How to Apply

Applicants should have a first or upper second class honours degree or equivalent in a relevant area. Applicants with a relevant Master's degree are particularly welcome. Applicants should possess excellent academic writing and English language communication skills and an ability to work to deadlines.

Apply Now

Those called for interview will be required to prepare a presentation.

Closing Date: February 2020

Interview date: Week commencing 16 March 2020

Start date: September 2020

Eligibility and Funding

Suitably qualified candidates worldwide may apply, although international students must self-fund the difference between the International and the UK/EU fee rate

£15,009 per annum stipend – stipend will be paid at the 2019/2020 UK Research & Innovation rate (https://www.ukri.org/skills/funding-for-research-training/).

Governance of Parliamentary Institutions: Structures, Processes, and Leadership

PhD GTA Funded Studentship

Reference Number: COSS2019-1

Project Leads: Dr Mark Bennister, Dr Samantha Shave, Professor Matthew Hall

Overview

The School of Social and Political Science's newly established ParliLinc Group at the University of Lincoln is offering a fully funded PhD studentship in the area of Legislative Leadership and Governance. The successful candidate will work with staff in the ParliLinc Research Group to investigate leadership and governance of the legislatures at Westminster, Edinburgh, Cardiff, and Belfast.

This research project draws on multi-disciplinary expertise across law, politics, and public policy to map the existing arrangements, place them in an historical context, understand internal dynamics and evaluate how parliaments build their collective identities, and understand how they establish public trust and manage their own reputations.

The project has the potential to impact on parliamentary governance in the UK and feed into comparative understanding of legislative administration and leadership. A strong research interest in legislatures (and preferably public leadership) and an aptitude for qualitative methods in particular is desirable. The successful candidate will be based in the new Lincoln Parliamentary Research Group  https://parlilinc.blogs.lincoln.ac.uk/), in the School of Social and Political Sciences. Within the broad parliamentary parameters of the project, the studentship will be able to pursue their own related research proposal.

Contact: Dr Mark Bennister: mbennister@lincoln.ac.uk

How to Apply

Applicants should have a first or upper second class honours degree or equivalent in a relevant area (e.g. law, political science, public administration, sociology, or public policy). Applicants with a relevant Master's degree are particularly welcome. Applicants should possess excellent report writing and English language communication skills, and an ability to work to deadlines.

Apply Now

Those called for interview will be required to prepare a presentation.

Closing Date: 12 March 2020

Interviews: provisionally week beginning 23 March 2020

Start date: 21 April 2020 or by agreement

Eligibility and Funding

Suitably qualified candidates worldwide may apply, although international students must self-fund the difference between the International and UK/EU fee rate. 

Home/EU fees will be covered by the studentship: £15,009 per annum stipend

The studentship may require you to offer up to 6 hours of teaching or related work per week, the income from which will go towards the cost of your tuition fees and any surplus fees will be paid by the College.

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Postgraduate Team
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