数学与计算机科学方向博士研究员

Doctoral Researcher (all genders welcome)

Georg-August-Universität Göttingen · 德国

原帖优先:申请材料、截止时间与资格以原帖和学校官方说明为准。

AI 中文速览

研究内容
开展概率论与随机几何方向的博士研究,重点关注大型随机系统的渐近性质,包括空间随机网络、随机几何、大偏差理论以及随时间演化的拓扑结构等。
申请条件
要求申请者持有数学、统计学或紧密相关领域的优秀硕士学位(或同等学历),具备扎实的概率论背景,对随机几何、随机图等领域感兴趣,并精通书面和口头英语。
待遇
提供75%的TV-L 13薪资级别岗位,岗位期限为3年。
申请方式
请通过电子邮件将申请材料打包为一个PDF文件发送至指定邮箱,截止日期为2026年10月12日。
材料清单
  • 个人简历 (CV)
  • 学位证书
  • 求职信
  • 一位推荐人的联系方式

由 gemini-2.5-flash-lite 生成,博士岗判定置信度 100%。

结构化信息

截止
(Europe/Berlin) 剩 5 天
学科
数学
合同类型
雇佣合同
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内容更新
导师
Christian Hirsch
来源
Georg-August-Universität Göttingen 官方招聘 · 最近核对 2026-10-07
判定依据(原文摘录)
  • is_phd
    Doctoral Researcher (all genders welcome)
  • english_ok
    are proficient in written and spoken English.
  • bachelor_ok
    hold an excellent or very good Master’s degree (or equivalent) in mathematics, statistics, or a closely related field
原文

At the University of Göttingen - Public Law Foundation – we offer a position in the research group of Prof. Dr. Christian Hirsch, Department of Mathematics and Computer Science, Institute for Mathematical Stochastics, starting January 1, 2027 or later as

Doctoral Researcher (all genders welcome)

- 75 % of pay grade 13 TV-L -

The vacancy is limited for 3 years. The position will be filled subject to the provision of the necessary third-party funding by the funding source.

About us: We develop probabilistic methods for understanding complex random structures, with particular emphasis on spatial networks, rare events, and time-varying topology.

The position: PhD in Probability and Stochastic Geometry. You will conduct research on asymptotic properties of large random systems and develop a doctoral project within the research group.

Particular emphasis will be placed on random systems whose geometry and topology evolve over time, with the aim of understanding both their typical asymptotic behavior and rare transitions. Research topics include spatial random networks, stochastic geometry, large deviation theory, and the probabilistic foundations of topological data analysis, with a current focus on time-varying topologies.

Projects may concern limit theorems for geometric and network statistics, large deviation principles and rare events, or probabilistic methods for persistent and dynamic topological summaries. You will participate in research activities at the Institute for Mathematical Stochastics and have opportunities for collaboration in Göttingen and internationally.

Your profile: As a successful candidate, you

• hold an excellent or very good Master’s degree (or equivalent) in mathematics, statistics, or a closely related field,

• have a strong background in probability theory, with interests in stochastic geometry, random graphs, large deviations, topological data analysis, or related areas,

• have strong motivation for mathematical research,

• are proficient in written and spoken English.

The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The University is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled people. In the case of equal qualifications, applications from people with severe disabilities will be given preference. A disability or equal status is encouraged to be included in the application in order to protect the interests of the applicant.

Please submit your application (CV, degree certificates, motivation letter and contact details for one referee) in one PDF document by

October 12th, 2026 via E-Mail: stochastik@uni-goettingen.de . Further information will be provided by Prof. Dr. Christian Hirsch via the same address.

Please note:

With submission of your application, you accept the processing of your application data in terms of data-protection law. Further information on the legal basis and data usage is provided in the Guideline for the General Data Protection Regulation (GDPR) https://uni-goettingen.de/GDPR

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