爱丁堡大学、曼彻斯特大学最新PhD奖学金项目信息

本期为大家推荐爱丁堡大学、曼彻斯特大学2024最新奖学金介绍。

1、爱丁堡大学

Machine Learning for Position Location

University of Edinburgh | School of Engineering

博导：Prof J Thompson, Prof T Ratnarajah

截止日期：June 30, 2024周天

资助的博士项目（全球学生）

About the Project

Position location, which in general comprises Direction of Arrival (DOA) and Time of Arrival (TOA) estimation, is an important area of research in many applications, including Radar signal processing and Fifth Generation (5G) and Sixth Generation (6G) commercial wireless systems. Conventionally this has been performed using either relatively simple algorithms based on received signal power measurement or more sophisticated subspace techniques, such as MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance techniques (ESPRIT). Recently, the implementation of position location estimation using Machine Learning (ML) techniques has been proposed as a methodology to improve performance beyond that of existing techniques, particularly in non-line-of-sight signal propagation conditions which occur commonly in many applications. This is an active area of research and is showing significant promise.

This project will run as part of the research council funded Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS).This is a four year programme involving both a PhD research project and integrated studies as part of a cohort of like-minded students.The integrated studies will include advanced courses and bespoke training events such as summer schools, specialised theme meetings, and innovation and commercialisation sandpits.

The project is sponsored by the company AMD and will involve close industrial collaboration to develop and test novel machine learning algorithms for position location. Following an initial literature review to define the state of the art, the following main research phases are expected:

• Determination of the specific application of position location estimation to be addressed within the project. This will entail basic application research and determination of current state-of-the-art techniques and future directions.
• Theoretical research into conventional position location techniques based on power measurement and subspace techniques. Here the objective is to establish performance and computational complexity benchmarks for a range of conventional techniques.
• Development of machine learning models suited to position location estimation and software implementation of these based on AMD computer processor and graphics processing unit (GPU) technology. These implementations will develop and optimize the machine learning models to determine relative performance and computational complexity when compared to conventional methods.

It is likely that the specific objectives of the project will evolve throughout the PhD. However, AMD believes that it is important that the project comprises both theoretical study of the candidate techniques and practical implementation on AMD hardware. Interested candidates are requested to apply as soon as possible.

Eligibility: An undergraduate degree in Electronics and Electrical Engineering, Computer Science, Physics or related discipline.
Applicants who require an ATAS certificate to work study in the UK will not be eligible for this PhD programme. A list of nationalities that do not require ATAS certification can be found here -https://www.gov.uk/guidance/find-out-if-you-require-an-atas-certificate

Further Information: PhD Project to be run through the Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS). For more information, please visit:https://spads.ac.uk/ The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here:https://www.ed.ac.uk/equality-diversity

Funding Notes

A successful candidate will receive an enhanced annual stipend of £20,716 tax-free, which is comparable with current graduate salaries and increases annually.Tuition fees + stipend are available for applicants who qualify as Home applicants. Applications will be considered from EU/International Students who meet the eligibility requirements.
To qualify as a Home student, you must fulfil one of the following criteria:

• You are a UK student;
• You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible.)

  2、曼彻斯特大学

The implementation and evaluation of a cohesive primary and secondary school emotional literacy curriculum to improve children’s emotional wellbeing

The University of Manchester|Faculty of Humanities Doctoral Academy, School of Environment, Education and Development

博导：Dr Charlotte Bagnall, Prof Neil Humphrey, Dr Nick Garnett

截止日期：June 28, 2024 周五

资助的博士项目（全球学生） 

About the Project

This fully funded ESRC CASE PhD studentship is at the centre of a collaboration between the#P-S WELLSprogramme and Whitefield Primary School, to enhance understanding of how to best support children’s emotional wellbeing over the transition from primary school to secondary school. The PhD will generate important new insights into the role of emotional literacy over primary-secondary school transitions (e.g., what specific theoretical components of emotional literacy programmes are important over primary-secondary school transition, and how do they drive outcomes); applied evidence generation (e.g., inequalities in emotional wellbeing trajectories across primary-secondary school transition; whether an emotional literacy intervention ultimately improves emotional wellbeing for all); and, policy and practice (e.g., implications for schools and professionals). Envisaged is an interdisciplinary, mixed-methods project, it will blend secondary analysis of a large quantitative dataset (#P-S WELLS) and new qualitative and quantitative data generation, comprising 3 empirical papers: (1) quantitative outcome evaluation of the efficacy of the emotional literacy curriculum; (2) qualitative process evaluation of factors which might affect successful implementation of the emotional literacy curriculum;and (3) mixed-methods investigation of the causal structures and antecedents of positive transition outcomes and maintenance of emotional wellbeing during and between primary and secondary school.

In addition to expert academic supervision at the University of Manchester (Dr Charlotte Bagnall and Professor Neil Humphrey; Manchester Institute of Education) and Nottingham Trent University (Dr Nick Garnett; Department of Psychology), the PhD student will also sit within the nationally renowned programme design and implementation team at Whitefield primary school, under the supervision of Mrs Marie Beale.

Eligibility Criteria

Academic and additional criteria:

• Bachelor's (Honours) degree at 2:1 or above (or overseas equivalent).

• ESRC-recognised research methods Masters degree (in a relevant discipline) with an overall average of 60% or above, and a minimum mark of 60% in your dissertation (or overseas equivalent). NB: priority will be given to candidates able to demonstrate expertise in both quantitativeandqualitative methods.

• Demonstrable experience conducting qualitative and/or quantitative applied research.

• Demonstrable experience working with schools.

In addition to the above, international applicants must provide one of the following:

• IELTS test minimum score - 7.0 overall, 7.0 in writing, 6.0 in other sections.

• TOEFL (internet based) test minimum score - 100 overall, 25 in all sections.

• Pearson Test of English (PTE) UKVI/SELT or PTE Academic minimum score - 76 overall, 76 in writing, 70 in other sections.

• You have taken an undergraduate or postgraduate degree in amajority English speaking nationwithin the last 5 years.

• Other tests may be considered.

The application deadline will beMidnight (GMT) on 28/06/2024. All supporting documents must be received by the deadline and sent as a zip file toHUMS.doctoralacademy.admissions@manchester.ac.uk, using‘ESRC NWSSDTP CASE Charlotte Bagnall'as the email subject.

Application procedure

The application must include:

• An up to date academic CV, detailing your education and qualifications; employment history; publications; and any other relevant information.

• A copy of your Bachelor’s and Master’s academic transcript and degree certificate. If your Master’s degree is pending, please provide an interim transcript.

• Supporting statement of a maximum of 400 words indicating why you would like to undertake this studentship and explaining how your focus, experience, and skills link to the research outlined above.

• Example of a piece of academic writing produced by you of up to 3,000 words (you may consider submitting two shorter pieces if these deal separately with conceptual and empirical analyses). This may be an academic essay or chapter(s) from a dissertation, in which case, an abstract or introduction outlining the context/aims/research questions of the study must also be included.

• Names and contact details of two academic referees who can comment on your suitability for PhD study and to undertake the advertised project.

• You must also submit the ESRC NWSSDTPEqual Opportunities Formswith your documentation.

Further information

If you have any questions about the project or would like to discuss this further, please contact Dr Charlotte Bagnall (charlotte.bagnall@manchester.ac.uk).

Formal Interview: Interviews are expected to take place on 9 July 2024.

Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. As an equal opportunities institution, we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Funding Notes

ESRC NWSSDTP CASE Award with Whitefield Primary School. A fully funded Studentship to commence in September 2024 covering tuition fees and an annual stipend (£19,237 for 24/25).