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PhD studentships

We offer a range of PhD studentships starting this January with the School of Built Environment and Architecture. Find out more below. https://apply-ukapplications.lsbu.ac.uk/signin
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Automated Detection of Contractual Risk Clauses in Construction Projects by using Natural Language Processing

Funded PhD Project (UK Students Only)

London, United Kingdom, Construction Project Management, Contract Management, NLP, AI

About the Project:

LSBU is a modern university with a mission to transform lives, communities, businesses and society through applied education and insight. We strive to influence the wider world and to positively impact on the society around us. LSBU’s PhD Scholarships are central to this vision.

LSBU is an inclusive and welcoming organisation, committed to eliminating discriminations. This means that we work pro-actively to eliminate individual, institutional, and systemic inequalities. We believe that it is not enough just to eliminate discrimination but that we must speak out and act against inequalities wherever and whenever they occur.

Doctoral Scholarship (with stipend): Total studentship cost of £25,900 per FT PGR, including a yearly stipend (£18,622), inside London allowance (£2,040), supervision costs (£2,618), support, training, and printing costs (£1,620), and the cost of a laptop in the 1st year (£1,000). Studentships will be funded for three years only with expected submission in Jan 2027 and viva, corrections and award completed before Dec 2027. The successful candidate will need to be enrolled for a January 2024 start.

School/Division: School of the Built Environment and Architecture/Construction, Property and Surveying

Duration of Scholarship: Full-time. It is expected that those awarded scholarships will submit their thesis no later than three years from enrolment.

Fully funded PhD studentship (home fees only) at London South Bank University, School of Built Environment and Architecture January 2024 Start. The student will be supervised by Dr Yuting Chen (https://peoplefinder.lsbu.ac.uk/researcher/89099/dr-yuting-chen) and Prof. Chika Udeaja (https://peoplefinder.lsbu.ac.uk/researcher/8q10z/professor-chika-udeaja)

Closing date for applications: 5th November 2023 by 11.59 pm

Start date: no later than 5th January 2024

Applicants are invited for a full-time three-year PhD studentship in the School of the Built Environment and Architecture at London South Bank University (LSBU) to begin no later than 5th January 2024. We are seeking an exceptional and enthusiastic person to join our team Construction Project Management research team in the School of the Built Environment and Architecture for creating an automatic contract review system for proactive risk management and dispute avoidance.

Project description:

Procurement and contracts are important in managing construction projects, especially risk management. However, previous manual review processes and early AI-based are known to be time-consuming and error-prone and do not address the huge data generated during the contract or procurement processes. Also, construction projects have suffered long from contractual risk, which will cause disputes in the future.

The normal contract document reviewing process to reduce risk has long been labour-intensive and can cause errors. An AI-automated detection method that addresses contractual risk and incorporates scope 3 emissions requirements is needed to address our current challenges in procurement and contracts.

The proposed project aims to develop an AI-powered contract specification classification model to automatically detect the contractual risks and the risk-taking party from each contract clause to help review the contract and reduce potential disputes in the future. The methodology adopted in this research will combine behavioural and design science.  The behavioural science will be used to explore the challenges, and the design will be used to develop system development of the AI-powered Natural Language Processing.

Eligibility: The successful candidate will have a BSc and ideally, an MSc, in Construction Project Management or related discipline with strong research methods skills. Candidates with programming background, especially with experience using LLM, are preferred. Candidates should have an interest in contract and procurement management in construction projects as well as an ability to work independently and with initiative at a high level of self-motivation. The studentship will be awarded based on merit for full-time study three years only. The studentship is limited to home students.

Contact for informal enquiries: Please contact Dr. Yuting Chen on email: cheny22@lsbu.ac.uk

How to apply: Please send your CV and personal statement (including motivations for studying at doctoral level, interest and experience in this subject area, research skills and experience, your programming, coding experience and suggestions for how an element of the proposed PhD could be explored) via email to Dr. Yuting Chen via email: cheny22@lsbu.ac.uk

Shortlisted candidates will be contacted with an invitation to attend an interview during the week commencing 13th November 2023. The successful candidate will be selected for the award in accordance with the University’s postgraduate admissions requirements and must be eligible under the Educations (Fees and Awards) Regulations 1997.

Closing date for applications: 5th November 2023 by 11.59pm

PhD studentship in digital design of biopolymer structural components for additive manufacturing

PhD studentship – 3 years full-time, commencing January 2024

About the role

An enthusiastic and highly motivated candidate is sought to support an ongoing research initiative at London South Bank University into the additive manufacture of thermoplastic structures. The project team at LSBU represents a coalescence of expertise in structural mechanics, additive manufacturing, artificial intelligence and digital design, with additional support and direction to be provided by our industrial partners.

Thermoplastic biopolymers hold great potential in the drive for net zero in construction and in fostering greater material circularity, while the development of digital design methods for 3D printing promotes the use of automated methods in structural design and construction practice. This project aims to refine a digital design method developed at LSBU for the robotic additive manufacture of structural-grade components from biopolymers or other thermoplastics derived from natural sources, e.g., cellulose. The predictive power of numerical models is to be enhanced through the use of machine learning, allowing greater flexibility and reliability in the digital design of polymer structural elements such as lightweight joists, bespoke structural connections, retrofitted components and load-bearing architectural features.

The successful candidate will be responsible for conducting structural analysis via finite element modelling of component geometries and structural optimisation informed by experimentally determined material behaviours. The candidate is expected to have some experience in the use of structural-mechanical analysis (finite element analysis) software in the context of structural or mechanical systems. In addition, knowledge of automation through scripting in languages like Python or C# (or similar) is desirable in order to run optimisation routines effectively. Some familiarity with machine learning or similar artificial intelligence approaches would be ideal, but training in this regard can be provided during the studentship. The successful candidate should be motivated to conduct their research independently and be comfortable liaising and working with stakeholders under the supervision of the Director of Studies (Dr Finian McCann) and the co-supervisors (Federico Rossi, Dr Luis Santos).

The work you will do

This role requires a very good MEng (1:1 / 2:1) or MSc (Merit or Distinction) graduate with proven experience in computational analysis for applications in structural or mechanical design, or industry experience to an equivalent level. You will be expected to work with a high degree of autonomy and manage a varied workload effectively with regular progress review meetings. Additionally, there will be a need to communicate technical activities and tasks to both technical and non-technical stakeholders, including the industrial partners on this project. This includes the preparation of journal articles, technical reports for industrial partners, and conferences papers and presentations.

The skills and experience you will need to be successful

You will have proven experience of applying structural-mechanical modelling software, e.g., Abaqus, Ansys Workbench, Karamba, LS-DYNA, to an MEng / MSc research level, or in an equivalent industrial R&D environment. The right candidate should have strong expertise in computational structural or mechanical analysis applied to structural design and/or mechanics with coding and automation skills, preferably in Python, C# or Rhino SDK.

Details about the role and How to apply

This is a full-time position funded for three years. The successful candidate must be enrolled before the end of January 2024.

For an informal discussion, please contact:

Dr Finian McCann mccannf@lsbu.ac.uk

Associate Professor of Structural Engineering, School of the Built Environment and Architecture, London South Bank University.

Please note, the contact details listed are for enquiries only.

Interview and assessment process

It is expected that interviews will be held in early November 2023.

Tsunami Induced Scour; Development of a Prediction tool for Engineers.

Brief: Tsunami are one of the deadliest coastal hazards. Tsunami induced sediment scour at structure foundations is a major cause of structural failure during tsunami inundation events. Current engineering knowledge of the scour process is disparate and incomplete. This is due in part to the devastation caused by these waves rendering field surveys of limited use. Further the physical process of the scour is highly complex. This complexity means that numerical models are difficult set up and to run efficiently and physical models require large and specialized facilities too run. Thus, there is a lack of physical model data to understand the process and validate any numerical model. The practicing engineer is left with no way to predict the scour and therefore effectively mitigate structural vulnerability to it.

This project will look to provide a comprehensive look at the physical process and parameter sensitivity of tsunami scour at coastal structures. In addition, it will develop a design tool for practicing engineers to estimate the scour depth expected from a given tsunami event. This will be achieved through the combination of the analysis of an extensive unpublished data set of tsunami scour taken in a unique tsunami modelling laboratory and the development of a numerical model to extend the data and formulate a design equation.

Aims: To illuminate the physical process of tsunami induced scour at structures and develop a predictive equation of scour development and depth as a function of incident tsunami wave parameters.

Methods: The work will analyse an extensive laboratory data set of tsunami scour to illuminate the physical processes and influencing parameters. From this a numerical simulation will be developed and validated using the open source CFD software OpenFOAM. The numerical model will then extend the laboratory data to conduct a comprehensive parametric study of tsunami scour. From this a regression analysis will be performed to isolate the influencing parameters and develop a predictor equation.

Funding: The funding includes a yearly stipend (£18,622), inside London allowance (£2,040), support, training, and printing costs (£1,620), and the cost of a laptop in the 1st year (£1,000). Funding is per year for three years full time home students only. The successful candidate will need to be enrolled for a January 2024 start.

Application Process: To apply upload your CV and complete this informal application https://forms.gle/qffx7GZkVDxBPRmX6

Applicants require a Bachelors (2:1 or better) or Masters degree in Civil engineering or a related field. This may include, but is not limited to Mechanical Engineering, Ocean and Coastal Engineering Physics, Earth and

Environmental Sciences and Mathematics.

Closing date Wednesday 01 November.

You will be contacted via email if you are shortlisted for interview. We aim to complete the shortlisting process within 1 week of the advert closing date (1 November). LSBU's on-line postgraduate application form will only be completed by the successful candidate after selection. The successful candidate will need to be enrolled from January 2024 due to the conditions of the scholarship.

Informal enquiries to Dr David McGovern, mcgoverd@lsbu.ac.uk

A low carbon, Artificial Intelligence based engineering system to monitor environmental noise.

Part funded PhD studentship.

This PhD research programme studentship is being offered by Dr Haydar Aygun at School of Built Environment and Architecture, London South Bank University Academic staff : LSBU People Finder

Background and rationale: Currently there are not any time efficient and low carbon acoustic system to monitor adverse changes in the built environment. There is a need for an engineering system to monitor adverse changes in the built environment.

Traditional environmental noise monitoring systems measure sound levels, store the data on internal memory card. Then the data is transferred to computer for analysing environmental noise parameters. They are expensive, time consuming, and contribute to carbon emission, especially for long term measurements. The costs of such a system are prohibitive, especially for developing countries. There is a need for a low cost, time efficient, and low carbon engineering system utilising artificial intelligence (AI) and machine learning algorithms to monitor environmental noise remotely.

Aims: This PhD programme aims to design, build, and test an intelligent low-cost and low carbon noise monitoring system using green technology. The low carbon system will be capable of monitoring environmental noise for a longer

period.

Methods: There is a growing need (regulation-driven) to monitor airports with a low cost, robust, and simple system. The AI and machine learning algorithms will be mitigating most of the laborious work. The expected research impact will show how such a system could be implemented around a noisy environment such as an airport to monitor environmental noise. An environmental sound monitor will be built and programmed using low-cost commercial electronics such as MEMS microphones, drastically reducing the cost of implementation. The system developed will be tested to international standards for compliance. Another new aspect of this research is that the system will be networked to create a platform. This platform would capture the sound environment and tag sound event spectrograms at the local level through Edge AI classification.

A central server will host the main AI. This will improve the accuracy of the classification through directed learning, without requiring user intervention. This will reduce the laborious nature of tagging unusual sound events which breach planning, construction, or demolition conditions.

Funding: The funding offered for this programme includes a yearly stipend (£18,622), inside London allowance (£2,040), support, training, and printing costs (£1,620), and the cost of a laptop in the 1st year (£1,000). This funding is per year for three years full time. The successful candidate will need to be enrolled for a January 2024 start.

The selected PhD student should hold a BEng in Mechanical Engineering (2:1 or better), MSc in Acoustics, and experience in environmental noise monitoring, acoustic product development, analysing noise data, machine learning, and acoustic modelling.

Closing date Wednesday 01 November.

You will be contacted via email if you are shortlisted for interview. We aim to complete the shortlisting process within 1 week of the advert closing date (1 November). LSBU's on-line postgraduate application form will only be completed by the successful candidate after selection. The successful candidate will need to be enrolled from January 2024 due to the conditions of the scholarship. Informal enquiries to Dr Haydar Aygun aygunh@lsbu.ac.uk.

PhD Studentship - Developing a Methodological Framework for the Industry 5.0-based Gamification of Construction Safety Education: Socio-Technical Perspectives

LSBU is a modern university with a mission to transform lives, communities, businesses and society through applied education and insight. We strive to influence the wider world and to impact the society around us positively. LSBU’s PhD Scholarships are central to this vision.

Project Description: The on-going drive to digitise the processes and products of the built environment in the UK is anchored on sustainability including carbon reduction. It is supported by Industry 4.0 through platforms like building information modelling (BIM), Smart Buildings and Digital Twinning. The BIM mandate of 2016 as well as the National Digital Twin Programme (NDTp), represent several routes towards digital transformation of the UK’s built assets. This project aligns with LSBU research areas such as digital transformation as well as health, safety, & wellbeing, by extending from the applicants’ prior research profile. It will strengthen the existing research at Centre for the Integrated Delivery of the Built Environment (IDoBE), which is uniquely placed to play a leading role in this regard.

The project is aimed at developing a framework for construction safety education through the integration of various digital technologies, especially BIM, VR and Industry 5.0; as well as the incorporation of behavioural aspects as well as scenario-based factors and construction methods. These technologies, factors and methods would holistically implemented in the framework including the gamification of scenarios in the VR platform.

Applicants are invited for a full-time three-year PhD studentship (International Students Only) in the School of the Built Environment and Architecture at London South Bank University (LSBU) to begin no later than 5th January 2024. We seek an exceptional and enthusiastic person to join our team in the School of the Built Environment and Architecture.

Duration of Scholarship: 3 years full-time in the School of Built Environment and Architecture at London South Bank University. The successful candidate must be ready to enrol in January 2024 and is expected to attend full-time for three years with thesis submission in January 2027 and viva, corrections and awards completed before Dec 2027.

Supervisor: The student will be supervised by Dr Zulfikar Adamu Academic staff : LSBU People Finder

Eligibility: Applicants should have a minimum of an upper second-class undergraduate degree, and ideally hold, or expect to achieve a merit or distinction in a master’s degree in a relevant subject from a UK university, or comparable qualifications from another recognised university. See: www.lsbu.ac.uk/international/your-country for guidance on entry requirements from different countries.

Application Process: Each application will be required to submit a proposal based on the project aim summarised above.

Shortlisted candidates will be contacted with an invitation to attend an interview during the week commencing 4th December 2023. The successful candidate will be selected for the award following the University’s postgraduate admissions requirements and must be eligible under the Education (Fees and Awards) Regulations 1997.

For informal enquiries about the project, contact Dr Amina Nazif (nazifa@lsbu.ac.uk). Applications submitted via email are NOT valid and will not be considered.

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