博士招生｜新西兰奥克兰大学、英国埃克塞特大学博士招生项目推荐

　　本期 “博士招生”为大家推荐新西兰奥克兰大学、英国埃克塞特大学博士招生项目，有需要或者问题的同学欢迎在 “文末扫码”：预约小曼博士1对1免费咨询哦~

　　

　　1

　　The University of Auckland

　　奥克兰大学

　　奥克兰大学（The University of Auckland），简称奥大，全球著名大学，坐落于新西兰第一大城市奥克兰市，拥有7个校区，是一所综合研究型大学，属于环太平洋大学联盟、Universitas 21、世界大学联盟，亚太国际教育协会、英联邦大学协会的成员。

　　2023QS世界大学排名第87位，2021泰晤士高等教育世界大学排名第147位，2021U.S. News世界大学排名第125位。

　　The overlooked X and Y factor in osteoarthritis?development

　　1?? Dr Raewyn Poulsen

　　2?? Sunday, April 30, 2023

　　3?? Competition Funded PhD Project

　　About the Project

　　Osteoarthritis (OA) is a leading cause of physical disability in adults worldwide. With no disease-modifying drugs to treat OA, patients typically suffer the pain and disability of disease for almost half their adult life. Women are more susceptible to OA than men and typically experience more severe symptoms, yet the opposite is true in animal models where OA shows a substantial male bias. This has meant that a considerable amount of current knowledge regarding OA pathogenesis comes from studies in male rodents. In our lab group, we study tissue from patients with OA.?Novel preliminary data from our lab indicates that some of the key pathways involved in OA pathogenesis differ between male and female patients with OA. This has important implications for understanding why women are more at risk of OA than men and for helping develop effective treatments for OA, potentially implying that different treatments may be required for females compared to males.

　　The objective of this project is to determine how the activity and function of key pathways involved in osteoarthritis pathogenesis differ between males and females. This is a first-in-kind study using a unique combination of molecular pharmacology and biomedical techniques. The project is at the intersect of biomedical science and pharmacology and will suit a student wanting to undertake a PhD in either discipline. This project will involve primary human cell culture from tissue obtained from patients with osteoarthritis as well as use of a range of molecular pharmacology and molecular biology techniques providing you with excellent training for your future research career.

　　We are looking for a high-achieving, motivated student with excellent organisational and time management skills. The successful applicant will have excelled in their Honours or Masters studies and have experience in one or more of the following:?cell culture, molecular pharmacology techniques (e.g alphaLISA), real time PCR, western blotting, reporter assays or transfection/viral vector-mediated transduction.

　　Because we know finding the right PhD project is important, informal enquiries from potentially interested students are welcomed. (Contact Raewyn Poulsen,?r.poulsen@auckland.ac.nz).

　　Funding Notes

　　This is a fully-funded PhD position supported by the prestigious Royal Society of New Zealand Marsden Fund. The successful applicant will receive a full scholarship covering personal living expenses. In addition, all compulsory fees for enrolment in the doctoral programme at the University of Auckland are covered for the three year period.

　　

　　2

　　University of Exeter

　　埃克塞特大学

　　埃克塞特大学（University of Exeter），又名埃克斯特大学，是一所位于英国西南部的顶尖公立综合性研究型大学。现为英国罗素大学集团、英联邦大学协会和GW4联盟等组织成员。

　　在世界大学排名中，埃克塞特大学长期居于前列，位列2023THE世界大学排名第137名，2023QS世界大学排名第163名。

　　埃克塞特大学商学院获得AACSB、EQUIS和AMBA三重认证的商学院，有着世界领先的研究水准。此外，学校在2020QS世界排名中拥有14个世界百强学科，在商科、艺术、教育、工程、法律、医学、科学、社会科学及运动科学等诸多学科领域均拥有世界一流的研究水平。

　　著名校友有《哈利·波特》作者J·K·罗琳，牛津大学现任校长安德鲁·汉密尔顿，皇室成员扎拉·菲利普斯等人。

　　Using Complex Networks and Machine Learning to Detect Situational Inauthentic Behaviour Online. PhD in Computer?Science

　　1???Dr Diogo Pacheco

　　2?? Sunday, April 30, 2023

　　3??Competition Funded PhD Project

　　About the Project

　　Location:

　　Department of Computer Science, Streatham Campus, Devon, University of Exeter

　　The University of Exeter’s College of Engineering, Mathematics and Physical Sciences?is inviting applications for a fully-funded PhD studentship to commence in September 2023 or as soon as possible thereafter. The studentship will cover tuition fees plus an annual tax-free stipend of at least ￡16,062 for 3.5 years full-time, or pro rata for part-time study.

　　Project Description:

　　Online social media have revolutionised how people consume information, and form and share their opinions. In a perfect world, this easy-cheap access to information would boost the global economy and the democratic processes. However, there is growing evidence showing the destructive power of malicious actors exploiting platforms' vulnerabilities and human's cognitive biases to nurture the current infodemic crisis.

　　The arms race between social media platforms and inauthentic accounts has already a long list of cycles. As usual, as technology develops increasing the capacity of detection, evaders also implement counter measurements creating more sophisticated deceivable agents. The literature already offers methodologies to detect different facets of this problem. For instance, (i) automated vs. organic, (ii) benign vs. malicious, (iii) coordinated vs. uncoordinated, and (iv) true vs. fake. These methodologies already empower us (the general public and the platforms) to combat fringe actors exploiting our vulnerabilities online. Unfortunately, none of these technologies is perfect, and bad actors often employ a hybrid approach mixing most of the above-mentioned facets.

　　Most of this technology relies on large amounts of historical data not only to build models for detection but also to perform “live” detection. Moreover, they tend to focus on labelling accounts rather than actions. For instance, Botometer, one of the most famous bot detection tools uses up to the last 200 tweets from an account in other to assess its “botiness”. Even though bot scores change over time, there is no association between an action or time leading to inauthentic behaviour. The project aims to evolve online inauthentic behaviour detection similarly as criminology has evolved from Lombroso's classical criminology school of thought which focused on traits of criminals to environmental criminology.?Can we develop a methodology to detect situational misbehaviour online?

　　The applicant should be willing to work with data science models, machine learning, network science, python programming language (desirable), statistical modelling and have a strong enough background in computer science and maths to enable the applicant to carry independent research.

　　Essential Criteria:

　　1. Strong data analysis skills demonstrated by academic excellence or practical experiences

　　2. Strong mathematical or statistical background, with the ability to conduct modelling

　　3. Programming skills, with a very good knowledge of Python or R

　　Desirable Criteria:

　　1. Experience of or ability to work with a large, varied dataset

　　2. Strong team player, communicator, and problem solver

　　3. Experience in generating, processing and modelling synthetic data

　　Entry requirements

　　This award provides annual funding to cover tuition fees and a tax-free stipend.?For students who pay tuition fees the award will cover the tuition fees in full, plus at least ￡16,062 per year tax-free stipend.

　　International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.

　　Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology.

　　If English is not your first language you will need to have achieved at least 6.0 in IELTS and no less than 6.0 in any section by the start of the project.

　　Alternative tests may be acceptable (see?http://www.exeter.ac.uk/postgraduate/apply/english/).