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liupkumse鐵蟲 (初入文壇)
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[交流]
英國斯旺西大學(xué)計(jì)算機(jī)系招收全獎PhD，聯(lián)邦學(xué)習(xí)方向
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大佬們好，在下目前有個英國斯旺西大學(xué)計(jì)算機(jī)系的全獎phd名額，獎學(xué)金涵蓋國際學(xué)費(fèi)和年度生活津貼，課題的主要領(lǐng)域是聯(lián)邦學(xué)習(xí)，提交申請的ddl是10月15日，入學(xué)時間是明年1月（別問我為啥時間這么緊張。。學(xué)校就是這么通知我的 ）。不過實(shí)在趕不上的晚一點(diǎn)入學(xué)，到明年5月入學(xué)季再來應(yīng)該也ok。該phd學(xué)制是4年，其中75%的時間做research，25%的時間做ta，ta期間可以拿到英國這邊的教師資格證，對畢業(yè)后有意在英聯(lián)邦國家做教職的同學(xué)比較有意義�？傮w而言英國這邊國際生獎學(xué)金的機(jī)會其實(shí)不太多，這幾年整體經(jīng)濟(jì)形勢也確實(shí)不太好，大學(xué)花錢都扣扣搜搜的，擠出來一個國際生獎學(xué)金名額也挺不容易的。目前這個獎學(xué)金cover每年20幾萬的學(xué)費(fèi)和每年18萬左右的生活費(fèi)，4年讀下來貌似也可以看作賺了150萬人民幣了？  項(xiàng)目具體信息請見附圖，歡迎感興趣的同學(xué)通過【郵件】與我聯(lián)系，郵件中可附上常規(guī)申請材料（成績單、cv等）。 【學(xué)校簡介】 斯旺西大學(xué)位于英國威爾士的第二大城市（cūn）斯旺西市（swansea）。該市是全英第五安全的城市，是個海濱城市，英國最美海灘之一的rhossili也在這。學(xué)校始建于1920年，qs 2025排名為298位�？傮w來說當(dāng)?shù)丨h(huán)境安全、風(fēng)景不錯、生活成本低、不卷（劃重點(diǎn)），學(xué)校的更多信息請感興趣的同學(xué)自行搜索。 【導(dǎo)師簡介】 dr. yang liu received his d.phil. in computer science from the university of oxford in july 2018. he is currently a senior lecturer in the department of computer science at swansea university. before joining swansea university, he served as an assistant professor at the harbin institute of technology in shenzhen from 2018 to 2024. his research interests focus on data security and privacy-preserving computing. he has expertise in federated learning, blockchain applications, and the design of privacy protection mechanisms. his current work explores the convergence of artificial intelligence and cybersecurity technologies, aiming to enhance the robustness and security of intelligent systems. 【項(xiàng)目簡介】 project description: the department of computer science of swansea university is offering graduate teaching assistantships for january 2025 entry to its phd studies in computer science. this position is ideal for candidates with a keen interest in pursuing doctoral research in cyber security, particularly focusing on privacy, security, and robustness in federated learning (fl). successful applicants will also have the opportunity to gain valuable teaching training and experience while developing their professional skills. the gta will complete the associate fellowship of advance he (afhea) and thereby develop their teaching related skills and enhance their professional competencies. the equivalent of 3 months per year will be devoted to teaching training/practice, the remaining time is for research studies on a four year programme. research topic: privacy and robustness in federated learning as the deployment of federated learning (fl) expands across various domains, so do the challenges related to privacy, security, and robustness. its distributed nature introduces unique vulnerabilities that traditional centralized learning approaches do not face. attacks on fl can result in significant privacy breaches, compromising sensitive data across multiple participants. this phd project focuses on the exploration and analysis of threats, attacks, and defenses within fl environments. the aim is to build a comprehensive understanding of the vulnerabilities in fl systems, design robust countermeasures, and establish guidelines for secure and privacy-preserving fl implementations. the project will not only focus on theoretical advancements but also emphasize practical applications in real-world scenarios. the successful candidates will have the opportunity to collaborate with a multidisciplinary team, including experts from both academia and industry, to ensure the research outcomes are both innovative and impactful.the ideal candidate should be passionate about tackling complex challenges at the intersection of ai, privacy, and security , and eager to contribute to both academic research and teaching. key objectives: 1. investigate federated learning threats: conduct a deep dive into potential attacks on fl systems, including poisoning attacks, backdoor attacks, and inference attacks. understand how these attacks exploit the distributed nature of fl to breach privacy and compromise model integrity. 2. design defensive mechanisms: develop advanced defense strategies against the identified attacks. this includes exploring techniques like differential privacy, secure aggregation, and adversarial training to enhance the robustness and privacy of fl models. 3. real-world application and validation: implement and test the developed models on real-world datasets from domains such as healthcare, finance, or iot. validate the effectiveness of the proposed defenses in preserving privacy and robustness under adversarial conditions. contact details for enquires: dr. yang liu https://yangliu.info 更新一下，申請DDL推遲到了10月23日。國際生建議選擇4月入學(xué)，以預(yù)留充足的時間申請ATAS和VISA。具體項(xiàng)目信息可見官網(wǎng)鏈接： 官網(wǎng)鏈接 |
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liupkumse
鐵蟲 (初入文壇)
- 應(yīng)助: 3 (幼兒園)
- 金幣: 215
- 帖子: 32
- 在線: 30.3小時
- 蟲號: 2543003
- 注冊: 2013-07-12
- 性別: GG
- 專業(yè): 計(jì)算機(jī)軟件
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申請截止日期延長至10月23日，獎學(xué)金詳情請見官網(wǎng)鏈接 獎學(xué)金官網(wǎng)鏈接 https://www.swansea.ac.uk/postgr ... r-science-rs699.php |
2樓2024-10-11 00:05:09
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