海外全奖博士招生信息汇总·第109期：荷兰代尔夫特理工、阿姆斯特丹、香港大学等等
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目录 Catalogue
1. 荷兰代尔夫特理工大学招全奖博士生
2. 香港大学李骁博士大学招全奖博士
3. 阿姆斯特丹大学招全奖博士生
4. 马斯特里赫特大学招收全奖博士生
01
荷兰代尔夫特理工大学招全奖博士生
职位信息
Phd position Integrated Smart Gate Driver for SiC Inverters in EV
Challenge: Integrated Smart Gate Driver for SiC Inverters in EV.
截止日期：2023年7月3日
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Job description
SiC inverters are an essential part in the EV motor system. As SiC technology is still not very matured nowadays, a smart gate driver to drive the transistors efficiently while monitoring the state-of-health would be beneficial. Meanwhile, issues related to EMI, over-voltage/current protection, short-circuit protection should also been taken care of. In this project, a highly integrated, multi-functional smart gate driver will be proposed to tackle these issues.
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Requirements
The candidate should have very good analog integrated circuit design background. Basic Basic knowledge in power conversion systems such power inverters needed.
The candidate should be highly self-motivated.
The candidate should be a team player.
The candidate needs to have good experience with IC design software Cadence Spectre. Tapeout experience is highly appreciated, although not a must.
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Additional information
In The Netherlands, almost all PhD positions are linked to funded research projects. This has several implications:
PhD students are employed: they receive a salary rather than a grant. Most projects have a duration of 4 years.
For more information about this vacancy, please contact Dr. Qinwen Fan q.fan@tudelft.nl.
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Information
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
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职位信息网址
https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=11959&jobTitle=Phd%20position%20Integrated%20Smart%20Gate%20Driver%20for%20SiC%20Inverters%20in%20EV
02
香港大学李骁博士大学招全奖博士
职位信息
香港大学李骁博士招收全奖博士生
1
导师介绍
李骁博士，香港大学土木工程系，助理教授。
Research lnterests:
Construction industrialization & informatics
Smart work packaging methodology
Advanced Al & robotics in industrialized construction
Advanced construction project management
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招生方向
人机协作︰模块化建筑装配机器人、绳驱动机器人(CDPR)等机构设计、子系统开发等;
专分布式协同:模块化建造分布式场景下区块链共识机制、激励机制设计、联邦学习等。
对于课题组另外两个方向感兴趣的也欢迎咨询:
进度优化:模块化建筑生产、运输、安装中涉及的组合优化、随机优化、启发式优化等问题;
知识图谱:模块化建造场景下复杂任务/工艺/故障语义丰富、因果学习、知识蒸馏等。
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如何申请
有意向申请人可将个人简历发送至shell.x.li@hku.hk，也可通过邮箱进一步咨询了解。
请在邮件标题中注明相关申请职位，并在邮件中说明来自connectEd
03
阿姆斯特丹大学招全奖博士生
职位信息
Seven PhD positions in AI for Fintech
Faculty/Services: Faculty of Science
截止日期：2023年5月21日
1
The Mission:
Want to become part of a dynamic community that is at the forefront of AI-driven Fintech innovation? Our experts from the Faculty of Science (with the Informatics Institute, the Institute for Logic, Language and Computation and the Korteweg de Vries Institute), the Faculty of Economics & Business (Amsterdam Business School and Amsterdam School of Economics) and the Faculty of Law (Institute for Information Law, Amsterdam Center for Law & Economics), are collaborating with leading Fintech companies and (regulating) organizations to develop cutting-edge AI solutions to solve complex problems in financial technology. Are you ready to be part of this exciting ecosystem and take your career to the next level? If so, we would like to invite you to apply for one of our seven PhD positions described below.
2
projects
Project 1: Knowledge-Driven Learning for XAI in Fraud Detection
In this project we aim to develop a novel neuro-symbolic framework that mainly combines the strengths of both the data-driven approaches (which comes with adaptability, autonomy, and good qualitative performance) and the knowledge-driven approaches (which comes with interpretability, maintainability, and well-understood computational characteristics) to provide explanations for experts in terms of relevant features and the structures in-between.Supervisors: Erman Acar (IvI/ILLC), Ilker Birbil (ABS)External partners: Mollie, ING
Project 2: AIDA: Artificial Intelligence for Due-diligence Analysis
In this project, we aim to develop information retrieval and natural language processing technology for e-discovery and due diligence analysis on legal and financial textual documents, and to support legal professionals searching for very specific information in huge sets of disclosed documents
Supervisors: Marc Francke (ABS), Jaap Kamps (ILLC)
External partners: Imprima, Zuva AI
Project 3: Learning High Dimensional Contagion Processes in Finance and Insurance
Multivariate contagion processes, e.g., those of the Hawkes type, have found widespread applications in finance and insurance, most noticeably for the modeling of systemic risk build-up. Whereas much progress has been made in exploring the underlying probabilistic properties, aspects of learning are still in their infancy. This project focuses on statistical learning for multivariate contagion processes, with a special focus on the practically highly relevant setting of many interacting components and high-dimensional processes.
Supervisors: Roger Laeven (ASE), Michel Mandjes (KdVI)External partner: Association of Insurers
Project 4: Robust fraud detection through causality-inspired ML
Payment platforms like Adyen use technology to efficiently detect fraud. Fraud detection is challenging, since both the genuine and fraudulent customer behavior changes over time and across markets. Machine learning is crucial for this task, but current methods are susceptible to learning spurious correlations. The goal of this project is to leverage causality-inspired machine learning methods to improve the robustness of fraud detection methods to distribution shifts.Supervisors: Sara Magliacane (IvI), Ana Mickovic (ABS)External partner: Adyen
Project 5: Systems for AI Data Quality in Finance
The impact of data errors on the output of AI models is difficult to anticipate and measure, and these errors can negatively impact regulatory compliance. Therefore, this project aims to enable non-technical users to validate and increase the quality of their data. For that, these users should be able to express data quality rules in natural language. We will design a data driven approach to leverage such rules to assist a domain expert to finetune data quality rules and “stress test” downstream AI models. This project favors a strong data engineering background combined with an interest to engage with European regulation applicable to financial data.Supervisors: Sebastian Schelter (IvI), Kristina Irion (IViR)External partner: ABN-AMRO
Project 6: Environment, Social and Governance (ESG) regulation impact on financial stability
In this project, we will analyze the driving factors behind ESG ratings via ML and XAI which will lead to a clearer understanding of how companies will be affected by ESG regulation. The insights gained from this analysis will allow us to study the effects on financial stability in a simulation study using agent-based models under realistic settings derived from empirical analysis.Supervisors: Simon Trimborn (ASE), Debraj Roy (IvI)External partner: ING
Project 7: HyperMining: Explainable Anti-Money Laundering using Process Mining on Hypergraphs
In this project we aim to develop an innovative Anti-Money Laundering methodology using advanced AI methods using hypergraph representations and process mining which can give an integral view of the transactions involved, deal with the inherent complexity of the data, and still be understandable for the experts analyzing the data so they can substantiate their decisions.Supervisors: Marcel Worring (IvI), Michael Werner (ABS) External partner: Transaction Monitoring Netherlands
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Tasks and responsibilities:
We are looking for a candidate with:
an MSc in computer science, mathematics, finance, econometrics, or a related field;
a strong scientific interest in AI and fintech and potentially data engineering;
strong academic performance in university-level courses in the relevant subjects;
experience in programming, software development, and data science tools
professional command of English and good presentation skills;
the willingness to work collaboratively with other researchers and external stakeholders;
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Our offer
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is as soon as possible. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,541 in the first year to € 3,247 in the last year (scale P). UvA additionally offers an extensive package of secondary benefits, including 8% holiday allowance and a year-end bonus of 8.3%. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
Multiple courses to follow from our Teaching and Learning Centre;
A complete educational program for PhD students;
Multiple courses on topics such as leadership for academic staff;
Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
7 weeks birth leave (partner leave) with 100% salary;
Partly paid parental leave;
The possibility to set up a workplace at home;
A pension at ABP for which UvA pays two third part of the contribution;
The possibility to follow courses to learn Dutch;
Help with housing for a studio or small apartment when you’re moving from abroad
5
职位信息网址
https://vacatures.uva.nl/UvA/job/Seven-PhD-positions-in-AI-for-Fintech/768660802/
04
马斯特里赫特大学招收全奖博士生
职位信息
PhD Candidate in the field of AI in education
截止日期：2023年5月31日
1
Project description
The Research Centre for Education and the Labour Market (ROA) of Maastricht University’s School of Business and Economics (SBE) and the NOLAI lab at Radboud University in Nijmegen are seeking to appoint a PhD candidate in the field of AI in education.
Nowadays, there are many concerns about the quality of education and the level of the basic skills of mathematics and language of children. Schools very often choose to use adaptive learning technologies with AI (ALTAI) to work on basic math and language skills. However, ALTAI is often not effectively used from a pedagogical/didactical point of view, since its effects are highly dependent on how it is used and which (pedagogical) purpose it is intended to serve. Furthermore, student cognition and personality traits may very well moderate effects of AI solutions in education: not all students have, for example, the required level of conscientiousness to use ALTAI in an effective way or have the grit to handle the freedom of selecting the right exercises. This relates to self-regulated learning and agency. Also, it is unclear how the increased use of AI and the differences in use and outcome for different types of students relate to the overarching question of inequality in education. Finally, the role of the teacher may be crucial to obtain positive effects of AI in education, as the teacher can overrule the ALTAI in amount of freedom given to de student or in (level of) exercises that are chosen.
This PhD-project aims to unravel the influence of ALTAI on reducing those differences in learning outcomes that are due to students’ socio-economic status (SES), and the relation of personality traits with effective use of adaptive AI, with the right amount of agency for both student and teachers. In doing so, we will be able to explain differences in the use and effectiveness of ALTAI in primary and secondary education and study how this relates to potential inequality in education.
Combining existing large datasets, this project has the unique opportunity to learn from bringing different sources of information together that until now have not yet been combined. This entails both usage as well as performance data from ALTAI programs in education, data from student admin systems on characteristics and background of students, and data from longitudinal data collections on for example student performance in math and language, as well as personality of students.
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Qualifications
Are you self-motivated, curious and interested in research? Are you excited to work in an international project team for an origination that is of societal significance? Do you have the skills required to become an excellent researcher in your field? Then a PhD position at NOLAI / ROA-SBE might be the challenge you are looking for.
Candidates will be selected on the basis of the requirements outlined below. To be considered, candidates should make sure that their application demonstrates how they meet these requirements:
You have a MSc degree in educational science or in (educational) psychology, sociology or economy or expect to graduate soon.
You have a strong academic background and willingness to publish in high-ranking academic journals;
You have excellent quantitative and analytical skills, as well as oral communication and writing skills;
Comprehension of the Dutch language is considered an advantage;
You have affinity with empirical analyses based on large data sets
You have knowledge of statistical software (e.g., Stata, R, Python, SPSS);
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Terms and conditions
Fixed-term contract: 4 years.
Fixed-term contract: 4 years (with binding evaluation after 1.5 years).
The intended start date of the appointment is 1 September 2023.
Remuneration will be according to standard salary levels for PhD students starting with a salary of €2.541 with a yearly growth to € 3.247 gross a month (based on a full-time appointment). Each year the standard salary is supplemented with a holiday allowance of 8% and an end-of-year bonus of 8.3% of the yearly gross income.
You will be formally employed by Maastricht University, but you are expected to be present at least two days per week at NOLAI in Nijmegen as well as at least one day per week at ROA in Maastricht.
The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply.
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Information
Applications including a curriculum vitae and motivation letter can be submitted through Academic Transfer and should be received not later than 31 May 2023. Interviews will take place on Thursday 8 June 2023 at the NOLAI lab in Nijmegen.
For more information, please contact prof. dr. Carla Haelermans (carla.haelermans@maastrichtuniversity.nl) or prof. dr. Eliane Segers (eliane.segers@ru.nl).
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职位信息网址
https://www.academictransfer.com/en/327104/phd-candidate-in-the-field-of-ai-in-education/
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