格拉斯哥大学、奥克兰大学最新PhD招生和奖学金信息

本期为大家推荐格拉斯哥大学、奥克兰大学2024最新奖学金介绍。

1  、格拉斯哥大学

PhD in Engineering - Predictive maintenance, ageing and lifetime monitoring of superconducting cables in modern power network

University of Glasgow|College of Science and Engineering

博导：Dr Mohammad Yazdani-Asrami, Dr Wenjuan Song

截止日期：June 16, 2024 周六资助的博士项目（全球学生）

About the Project

Project background and aim

A fully funded PhD position for 3 years open to all international and home students to apply for with start date no later than 01 September.

The UK government has set a very ambitious target for CO2emission neutrality by 2050. To realise its target, a shift from fossil fuel energy production towards renewable energy resources is essential.

The massive rise in the share of onshore and offshore wind energy in total generation fundamentally reshapes the modern power system and significantly increases the need to build new HVAC or HVDC cable connections. It becomes more serious by new investment in offshore solar and energy generation in other continents as energy hubs.

Deployment of superconducting cables has been envisioned to be used for higher power transmission by increasing the transmitted current while keeping or even reducing the operating voltage. This is due to their technically-attractive features such as high-current capacity, very low losses, fault-current limiting capability, compact structure, and light-weight.Superconducting cable can be also used to transfer both electricity and energy-careers such as liquid hydrogen.

Artificial Intelligence and machine learning methods were utilized recently to analyse big sets of data and real-time measurements towards better understanding the behaviour of power grids. AI has been used in the area of protection for conventional systems for a wide range of purposes including derivation of fault levels, selection of settings, adaptive protection fault detection and classification. In this work, we will mainly discuss how AI techniques could help address the challenges in efficient ageing and condition monitoring for the protection of superconducting cables.

As part of this PhD programme, we will develop and validate predictive models for superconducting cables to assess the impact of different conditions on several cable properties while AI technology will add values to the results for lifespan expectancy estimation and ageing prediction in superconducting cables using measurements and machine learning technology.

This PhD programme is part of an EU Horizon funded project with 10 partners within EU. The student will also be in close interaction with the industrial partners involved in this project and will exchange knowledge with them regularly, offering a unique industrial slant to this studentship. There will be opportunities for research visits and also participating in international conference/workshop as part of this PhD to disseminate the findings and results of research work.

The student will experience cutting-edge research within a multidisciplinary team in “Propulsion, Electrification & Superconductivity” group and CryoElectric Research Lab, in which individuals from a diverse range of backgrounds are all supported to thrive.

The PhD student will join at an exciting time for the group, following substantial external investment in artificial intelligence and machine learning capabilities for superconducting applications that the research will integrate with. The group consists of about 10 researchers (PhD students, research assistants, visiting scholars and academics) conducting leading-edge research in applied superconductivity for large scale power applications. We collaborate with a range of academic and industrial partners within the UK and abroad (Italy, China, Japan, USA). There will be opportunities for the PhD student to be trained and to learn modelling techniques such as finite element modelling COMSOL.

More information about my own research and that of our wider group can be found at:

https://www.gla.ac.uk/schools/engineering/staff/mohammadyazdaniasrami/

The principal supervisor, Dr. Yazdani-Asrami, is a member of the Royal Academy of Engineering review team, EPSRC Peer Review College, Senior member of IEEE (SMIEEE), member of IET (MIET), member of CIGRE, member of British Cryogenic Council (MBCC), and member of Cryogenic Society of America (MCSA). He is an editor at Superconductor Science and Technology journal (IOP Publishing), World Journal of Engineering (Emerald Publishing), Aerospace Systems journal (Springer), International Journal of Aeronautical and Space Sciences (Springer), Superconductivity journal (Elsevier), and Transformers Magazine (TM). He also served as guest editor for several special issues in "IEEE Transactions on Applied Superconductivity" and "Superconductor Science and Technology" journals.

Eligibility criteria

Informal enquiries are encouraged and welcomed and should be directed to Dr. Yazdani-Asrami by sending a CV and a cover/intention letter. Please be to the point explaining how your previous experiences are well-aligned with this PhD position.

• The project calls for a student with an enthusiasm for working in large scale superconducting power fields with real-world applications, coupled with strong computer programming skills.

• Applicants should hold, or expect to receive (before start date), a master’s level qualification.

• Excellent time and project management skills are essential.

• This project will deal with signal processing and AI for regression, classification and clustering. A good background in coding (Matlab, Python, and/or C++) and AI/ML techniques would be essential.

• The ideal student will haveproven problem-solving abilities and an enthusiasm for innovation and creative and critical thinking.

• Prior knowledge of high voltage technology testing for ageing, and superconducting cable modelling or experimental experience would be desirable but not essential. Prior experience in cable manufacturing or high voltage testing would be a strong plus to the applicant’s case.

• Having publications in reputable journals in the field of applied superconductivity or high voltage technology is highly desirable.

• Non-UK applicants must meet ourEnglish language entry requirement. Excellent communication and interpersonal skills to integrate in the group is essential.

For more information, please check the University of Glasgow’s admission requirements.

How to apply

Please refer to the following website for details on how to apply:

http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/

NOTE: Before applying, please make sure to have informal discussion and meeting with Dr. Mohammad Yazdani-Asrami, as stated above in Eligibility Criteria. In addition, once you apply through the online portal, please forward your application reference number and CV toMohammad.yazdani-asrami@glasgow.ac.uk

Funding Notes

This prestigious PhD position is fully funded. Funding is available to cover tuition fees for 3 years (36 months from the start date of the project), as well as paying a stipend (£20,400 per year – tax free) and a generous budget for study running costs.

 2  、奥克兰大学

Understanding digestion through imaging and modelling

University of Auckland|Auckland Bioengineering Institute

博导：Assoc Prof L Cheng

截止日期：August 30, 2024 周五资助的博士项目（全球学生）

About the Project

Interested in a rewarding career in bioengineering? Get sponsored to do life-changing research in New Zealand!

Once food is ingested, the stomach serves as a reservoir and continues to break down the food into smaller particles until they are small enough to progress into the small intestine. The rate at which different types of foods break down is of great interest to food technologists, pharmaceuticals and bioengineers. Our research group has developed methods to image the contraction of the stomach in an MRI and have used these images to develop subject-specific computational fluid dynamics (CFD) simulations to improve our understanding of how stomach contractions mix and break down food.

In the next phase of this research, we seek to use MRI to track the breakdown of food contents over time, and the rate at which food empties from the stomach in both normal subjects and patients with chronic indigestion. New CFD simulations, such as with multi-phase flow interactions, will be developed to help interpret the stomach MRI data.

Desired Skills

Bachelor’s or Master’s degree in Engineering, Physics or equivalent. Experience with mathematical modelling, data analytics, image processing, computational fluid dynamics. Some familiarity with MATLAB, Python, and CFD simulations be desirable.

Find out more about this project and other projects on our website here：https://www.findaphd.com/common/clickCount.aspx?theid=165929&type=184&DID=53&url=https%3a%2f%2fwww.auckland.ac.nz%2fen%2fabi%2fstudy-with-us%2fstudy-options%2fresearch-projects.html

The Auckland Bioengineering Institute - breaking boundaries in bioengineering for more than 20 years

At the Auckland Bioengineering Institute (ABI), we apply engineering and technical innovation to advancing medical care, human capability, and understanding of human physiology. Our team of world-renowned researchers are working on everything from artificial intelligence avatars, to implantable devices, to digital models of the human body. Our focus on research excellence and commercialisation adds value to society and to the global economy.

Our research makes a real difference in the world. We’ve designed sensors to diagnose stomach disease without needing invasive surgery; developed a tiny wireless implantable device to measure brain pressure and save the lives of children with hydrocephalus; and we lead the world in building digital models of the human body which will enhance personalised medicine approaches for improved diagnosis and treatment.

Join our team of researchers for a postgraduate degree and together we can make a difference. Our graduates are amongst the most employable in the world - many either continue their career in research, find employment with industry leaders such as Rocket Lab or Fisher & Paykel, or launch their own startup companies.

Our students come from over 50 different countries and a wide range of backgrounds and disciplines, including Engineering, Medicine, Mathematics and Science.