海外博士项目招生信息汇总

今天机构申请部老师整理最新海外博士招生和奖学金介绍，同学们快看看有没有合适自己的项目吧！ 

目录

1.香港科技大学（广州）

2.澳门理工大学

3.美国宾夕法尼亚州立大学

4.意大利FBK研究所  

5.阿姆斯特丹大学  

6.代尔夫特理工大学

7.马普所

01 香港科技大学（广州） 职位信息

香港科技大学（广州）杨可洲助理教授课题组招收博士生以及科研助理

简介

香港科技大学（广州）功能枢纽微电子学域助理教授杨可洲课题组计划在2024年招收博士生（2名）及科研助理（2名）。研究方向为应用于神经形态计算（类脑计算）的自旋电子器件，通过根据算法需求探究合适的器件性质以及根据实际器件进行算法优化两个方向进行软硬件协同设计。

研究包括计算模拟（Python/Matlab）和实验（实验过程需要在超净间进行器件制备。

PI简介 姓名：杨可洲 职称：助理教授 香港科技大学（广州）功能枢纽微电子学域 杨可洲在2023年作为助理教授加入香港科技大学（广州）功能枢纽微电子学域。他于同年在宾夕法尼亚州立大学材料科学与工程专业获得博士学位。

此前，他在2018年于同济大学应用物理专业获得学士学位，于2019年在宾夕法尼亚州立大学获得材料科学与工程硕士学位。他的研究兴趣集中于可应用于神经形态计算（类脑计算）的新型器件。目前他的工作方向主要是应用于脉冲神经网络和贝叶斯神经网络的自旋电子器件的软硬件共同设计。他的工作同时包含计算模拟和实验。

Website:https://facultyprofiles.hkust-gz.edu.cn/faculty-personal-page/YANG-Kezhou/kezhouyang

招生要求

1.博士生须满足学校招生要求，详见： https://facultyprofiles.hkust-gz.edu.cn/faculty-personal-page/YANG-Kezhou/kezhouyang2.

2.具有物理、材料、电子信息工程或其他相关专业背景。

3.具有微纳电子器件制备加工经验的同学优先。

4.春季博士项目申请人需要在2024.1.8前于官网提交申请（即将截止）；秋季博士项目申请人需要在2024.7.15前于官网提交申请 https://fytgs.hkust-gz.edu.cn/admissions/before-submitting-an-application/admission-timeline

联系方式

欢迎感兴趣的同学通过邮件进行联系（邮件注明：姓名-博士生/科研助理申请）。  

邮箱：kezhouyang@hkust-gz.edu.cn

02 澳门理工大学

职位信息

澳门理工大学-沈定刚教授和檀韬副教授-联合招收医学人工智能全奖博士生

简介

沈定刚教授和檀韬副教授在澳门理工大学应用科学学院联合招收医学人工智能全奖博士生，2024年9月入学，奖学金每月2万澳门币，共3年，澳门理工大学应用科学学院博士生有机会同时获取葡萄牙科英布拉大学的博士学位。博士生候选人需要有至少一篇医学/自然图像人工智能领域中科院一区一作文章或者CCF A类一作文章。

沈定刚教授是上海科技大学生物医学工程学院的教授和创始院长、上海联影智能的联席CEO，也是IEEE、AIMBE、IAPR和 MICCAI的会士(Fellow)。曾任美国北卡罗来纳大学教堂山分校 (UNC-Chapel Hill)终身教授、冠名杰出教授，影像分析中心主任，IDEA Lab 主任。研究兴趣包括医学人工智能，影像分析、机器学习和模式识别。在国际期刊和会议上发表了 1500 多篇论文，H-index138，被引用8万多次。

现任 Frontiers in Radiology 主编、八个国际期刊副主编（或编委），曾任MICCAI董事会成员、MICCAI 2019总主席。 檀韬副教授是科技部一带一路项目专家、国家重大人才工程青年项目获得者，浙江大学本科、荷兰爱因霍芬理工大学硕士、荷兰radboud 大学计算机科学博士，曾担任通用医疗(GE Healthcare) 人工智能资深科学家。

主要从事医学影像上的人工智能前沿研究，发表论文100余篇，拥有16项美国专利（包括在审），以第一作者或者通讯作者在Cell 子刊 Cell Reports Medicine、Nature 子刊NPJ Breast Cancer、TMI、MEDIA等高水平期刊发表文章。

主导或参与美国FDA批准产品4项、欧盟CE批准产品2项、中国NMPA批准产品1项。 澳门理工大学是澳门政府大力支持的应用型综合性公立大学，秉承着以学生为本、质量立校的宗旨，提供学士学位及研究生课程。

澳门理工大学凭着多年来对办学素质的坚持，在院校评鉴及教学方面创下数个第一，包括成为亚洲首家以“充满信心” 的评级通过英国高等教育质量保证局评鉴的高等院校、澳门首家并唯一连续两度荣获“国家级教学成果奖”、以及全国唯一三度荣获“亚太教育质量奖”的高等院校，办学质量备受国际认可。

联系方式 请有兴趣的同学发简历到：taotanjs@gmail.com

03 美国宾夕法尼亚州立大学

职位信息

美国宾夕法尼亚州立大学(Penn State University)大学电子工程系和材料研究院，Ning Li教授课题组招收多名全奖博士生。入学时间为2024年秋季。  

简介   课题组目前致力于新一代人工智能计算和通信系统中的电子和光电子材料和器件的研究。

具体包括：

1) 新型存储器及其在存算一体和类脑计算中的应用

2) 互联与通信中的电子和光电器件

3) 器件与材料的异质集成

4) 宽带半导体和二维材料。  

ning li教授，于清华大学电子工程系获得学士与硕士学位，德州大学奥斯汀分校获得博士学位，曾在纽约州IBM T. J. Watson研究中心长期从事半导体和光电子学研究工作。研究成果发表于Nature Photonics, Nature Communications, Advanced Materials, Advanced Electronic Materials, APL Machine Learning 等知名期刊，以及IEDM, VLSI, OFC等国际会议。其工作曾被 Nature Research Highlight、Semiconductor Today、日经新闻等媒体报道。

获得美国专利200余项。多次获得 IBM 高价值专利奖、 发明成就奖、和发明大师奖。宾夕法尼亚州立大学 (Penn State University) University Park 校区坐落于宾夕法尼亚州Happy Valley, 是一所大型研究型大学，理工科科研资源丰富，其中材料科学与工程专业全美排名前十。

 联系方式  

欢迎具有相关专业背景的本科生、硕士生加入本课题组，特别欢迎具有电子工程，材料科学，物理，计算机等跨学科背景的学子。申请者请将个人简历（cv），成绩单和有关材料发至邮箱：nbl5288@psu.edu   更多信息， 请查阅课题组主页： https://sites.psu.edu/ningli

04 意大利FBK研究所 职位信息

意大利FBK研究所招收全奖博士

简介

实验室简介 3DOM Unit为意大利FBK研究所下辖的一个实验室，主要研究精确 3D 测量和基于现实的 3D 重建问题。在针对地理信息和地理空间问题开发计量解决方案和 3D 制图方法方面，3DOM Unit已获得了巩固的专业知识。地面、无人机、航空和卫星摄影测量以及三角测量和飞行时间激光扫描仪是我们获取 3D 度量和准确信息的来源。

该研究小组致力于工业计量、地理空间数据分析、传感器和数据集成、环境监测、3D变化检测、从图像和3D数据中导出度量和语义信息、测绘和测量、地理信息算法设计和实现、移动测绘和SLAM、GIS 和制图应用、文化遗产文献和数字保存、VR/AR 解决方案开发。目前小组正在积极开拓AI + 视觉领域的研究，包括3D渲染，3D生成，点云分类/分割等。

Prof Fabio Remondino于2006年在ETHZ取得博士学位，目前为3DOM Unit负责人，并且兼任University of Udine教授, 他本人在google scholar有2W+引用量。

实验室更多介绍详见：https://3dom.fbk.eu/home 导师google scholar： https://scholar.google.com/citations?user=s6R9byAAAAAJ 起始时间：24年11月1日，标准学制3年。

奖学金：全奖

优势：

1.国际化的团队，Lab成员来自8-9个不同国家，平时都用英语交流，可以锻炼你的英语和接触不同文化。

2.相较于内地PhD更加work life balance,工作之余时间可以拓展自己的兴趣。

3.老板在ETH, UC Berkeley, UC Santa Barbara 以及欧美众多名校均有connection, 期间有机会过去交换或者访学。

研究方向

transfer learning (zero shot learning), diffusion model application (AIGC, 3D rendering, 3D classification等)。 都是当前AI工业界的热门方向，需求量大，好就业，如果有自己其他idea可以在邮件跟老师交流。

招生要求

1.拥有硕士学历，英语达到欧标B2(IELTS 6.0左右), 硕士为英语授课者免除英语证明。

2.有deep learning / 3D点云 / computer vision, etc 相关研究或者工作经验，掌握python, 如果有相关论文发表会很加分。

3.自驱能力强，prefer self-motivated student，能力强的话可以跟组里其他小伙伴挑战下AI的几大顶会 。

联系方式

若有意向，请及时邮件联系remondino@fbk.eu，邮件名注明 “姓名+24fall PhD application”，附件请附上英文简历以及相关支撑文件。

05 阿姆斯特丹大学 职位信息

PhD positions in String Theory 3月4日截止

Job description

String theory is the most promising theory that unifies all particles and forces in nature, including gravity, in a way consistent with the laws of quantum mechanics and relativity.   String theory answers fundamental questions about the symmetries of nature, the quantum behaviour of black holes, the existence and breaking of supersymmetry, and the quantum treatment of singularities.   In string theory all the forces and particles emerge in an elegant geometrical way, realizing Einstein's ultimate dream of building everything from the geometry of space-time.

 Tsaks  

You will do original research in this field under the direction of one of the faculty members in the group.   You will be comfortable using mathematical tools on a daily basis to attack fundamental problems in theoretical physics.  

The daily activities consist mainly in research, but it is also expected that you participate in the many seminars by internal and external speakers as well as journal clubs and group activities.  

Collaboration with other PhD candidates, postdoctoral researchers and other faculty members will be encouraged.   At the end of the PhD program you will be an expert in at least one of the subfields of High Energy Theoretical Physics.  

While these topics are fundamentally of a theoretical nature, you will have the possibility to develop collaborations with other members of IoP and pursue applications of string theory techniques in other fields.

Requirements  

A masters degree, or equivalent, in physics   A good background in theoretical physics   the ability to work independently and to collaborate in a collegial research environment;   excellent written and oral English communication skills.  

职位信息网址   https://vacatures.uva.nl/UvA/job/PhD-positions-in-String-Theory/785935502/

06 代尔夫特理工大学

职位信息

Machine learning-enhanced numerical solvers for the shallow water equations   Affiliations:Group of Numerical Analysis1, Delft Institute of Applied Mathemat   ics2, Delft University of Technology (TU Delft), the Netherlands.  

Supervisors:

  (1) Prof.dr.ir. C. Vuik3, TU Delft (Group of Numerical Analysis).  

(2) Dr. A. Heinlein4, TU Delft (Group of Numerical Analysis).  

(3) Dr. J. Zhao5, TU Delft (Group of Numerical Analysis) and Deltares6.  

Address:Mekelweg 4, 2628 CD, Delft, the Netherlands.   Important note:The candidate will need to apply for the the CSC scholarship.  

Only if he/she obtains the CSC scholarship, he/she may start this project at TU Delft.   3月31日截止

Project  

The shallow water equations (SWEs) are widely used in modeling of rivers, lakes, oceans, etc.   They are derived from depth-integrating the Navier-Stokes equations and are suitable in thecase where the horizontal length scale is much greater than the vertical length scale.   Accurateand fast solvers for the SWEs have been investigated by many researchers in the past decades.   The new field of scientific machine learning (SciML) has recently evolved as a result fromthe increasing attention and success of machine learning, and it deals with the combinationof techniques from scientific computing and machine learning.   A typical example for SciMLapproaches is the enhancement of classical numerical solvers, for instance, for partial differentialequations, using machine learning techniques.  

One of the most popular fields of application ofSciML is computational fluid dynamics (CFD); see, for instance, the review paper.   The main target of this project is to explore the possibilities of enhancing the conventionalnumerical solvers for the SWEs by machine learning methods, e.g., graph neural networks(GNNs) [7], physics-informed neural networks (PINNs) [5, 8], etc. In particular, we aim atspeeding up the solving procedure of Delft3D Flexible Mesh7, which is an open source numericalsimulation software developed by Deltares. This software can simulate storm surges, hurricanes, tsunamis, detailed flows and water levels, waves, sediment transport and morphology, water quality and ecology.  

The users of this software include modellers, engineers and researchers from universities and consultant companies all over the world.   The key component of this software is the D-Flow Flexible Mesh module for the hydrodynamical simulation, which solves to SWEs using a finite volume method on staggered unstructured grids.   For time integration, a θ-method is used, such that the time step size is restricted due to theCourant–Friedrichs–Lewy (CFL) condition.  

Therefore, as an alternative, a fully implicit timeintegration method has been investigated at Deltares several years ago. However, the resultingsystem is highly nonlinear, such that the development of fast nonlinear solvers is required.  

Many different classical numerical approaches for improving the nonlinear convergence exist,however, we are aiming at novel approaches that improve the convergence of the nonlinearsolver using machine learning methods.  

One possible method has been introduced in , and this direction could be a starting point for this project.   We are also interested in new research questions that may arise during the work of this PhD project.

Requirements  

Below are some requirements on the candidate who would like to join this project as a PhDstudent:  

1.The candidate will need to apply for the CSC scholarship from China. Only if he/she

obtains the CSC scholarship, then he/she may start this project at TU Delft.  

2.The candidate should have good knowledge of numerical methods, machine learning, and

numerical programming/software development, in particular, Fortran and Python.  

3.As required by TU Delft, the candidate needs to show a sufficient English language levelbefore starting the PhD project. The requirement says:

• IELTS: Overall band score is 7.0 (with scores of at least 6.5 for all sections)
• TOEFL: Overall band score is 100 (with scores of at least 21 for all sections)

More detailed information could be found in.  

4.The candidate should obtain a master degree before starting the PhD project

Information  

Below is more information about this project:  

1.The duration is 48 months.  

2.The project can be started as soon as possible if the candidate meets the requirements inSection .  

3.The candidate will work in the Group of Numerical Analysis, Delft Institute of Applied   Mathematics in TU Delft.  

4.We will help the candidate with the research, aiming at journal papers as the outcome ofthis project.  

5.One goal of this project is that the candidate can obtain a PhD degree from TU Delft atthe end of the project.  

6.More details about the process of the four years PhD work in TU Delft could be foundin.

 Apply

If you are interested in working on this project as a PhD student, please send your CV and transcripts toC.Vuik@tudelft.nl,A.Heinlein@tudelft.nl, andJ.Zhao-9@tudelft.nl.

职位信息网址  

For the process of a PhD work in TU Delft, please see   https://www..nl/io/onderzoek/graduate-school/process-forms

07 马普所 职位信息

Ph.D. position (m/f/d) | Spintronics

3月31日截止  

Job description  

Spintronics uses electron spin to process information, going beyond traditional electronics.   It encodes data using both charge and spin, creating devices such as spin valves with reduced power consumption and increased processing speed.   Researchers are exploring materials and combining layers to manipulate spin orientations, driving advances in computing and memory as an interdisciplinary field combining physics, materials science and electrical engineering.[1-4].  

We are currently looking for aPh.D. candidate (f/m/d)who is interested in related research on spintronics.   The position will be based in Prof. Stuart Parkin’s Department Nanosystems from Ions, Spins, and Electrons (NISE) at theMax Planck Institute of Microstructure Physics, Halle (Saale), Germany focusing on research in spintronic, atomically engineered materials and topological materials.  

Tsaks  

Develop and optimize recipes to deposit functional thin films with cutting-edge integrated systems;   Investigate related deposition mechanisms with in-situ analysis tools;   Design, fabrication, and performance measurements of devices in collaboration with other colleagues.  

Requirements  

The candidate is expected to develop in-depth knowledge about thin film deposition and gain insight into the deposition mechanism by using in-situ measurements, as well as to apply this knowledge to the successful development and measurement of innovative, high-performant devices.  

The candidate should be highly creative, proactive, self-motivated, and capable of independent work beyond state-of-the-art objectives.   Active participation and engagement in the research activities of the group are highly desirable.   We seek candidates with

• A background in Chemistry, Materials Science, or Physics (Master’s degree or equivalent), knowledge in magnetism, spintronics or solid-state physics is desirable;
• Experience in spintronic device preparation and measurement is desirable, e.g. electron transport or MOKE;
• Knowledge of thin film deposition, characterization, and measurement is beneficial, e.g. ALD, CVD, PLD, sputtering, or MBE.

 职位信息网址 https://www.mpg.de/21471240/phd-position-spintronics

以上就是机构编辑部老师整理的海外博士项目招生信息汇总