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- Aufgaben: Join our research group to tackle cutting-edge problems in optimization and control of gas networks.
- Arbeitgeber: WIAS is a leading research institute in Berlin, part of the prestigious Leibniz Association.
- Mitarbeitervorteile: Enjoy a flexible work schedule and competitive salary under the German TVöD Bund scale.
- Warum dieser Job: Be part of an interdisciplinary team working on impactful projects in mathematical modeling and optimization.
- Gewünschte Qualifikationen: Master’s degree in mathematics or related field; strong background in optimization and PDEs required.
- Andere Informationen: Position available immediately; application open until filled.
Das voraussichtliche Gehalt liegt zwischen 36000 - 60000 € pro Jahr.
PhD Student Position (f/m/d) (Ref. 23/14) at WIAS, Berlin, Germany
The Weierstrass Institute for Applied Analysis and Stochastics (WIAS) is an institute of the Forschungsverbund Berlin e.V. (FVB). The FVB comprises seven non-university research institutes in Berlin which are funded by the federal and state governments. The research institutes belong to the Leibniz Association.
WIAS invites applications for a PhD Student Position (f/m/d) (Ref. 23/14) in the Research Group “Nonsmooth Variational Problems and Operator Equations” (Head: Prof. Dr. M. Hintermüller) starting as soon as possible.
The position is tied to the project: “Stochastic gradient methods for almost sure state constraints for optimal control of gas flow under uncertainty”, a subproject of the collaborative research center TRR 154: Mathematical Modeling, Simulation and Optimization Using the Example of Gas Networks. The collaborative research center is an interdisciplinary endeavor between the Weierstrass Institute, Humboldt University of Berlin, Technical University of Berlin, Technical University of Darmstadt, and Friedrich-Alexander University in Erlangen Nuremberg.
The goal of this project is the development of stochastic gradient methods for the treatment of almost sure state constraints. Such constraints arise, for example, in the nomination validation of gas networks under uncertain demands but also play a role in the transition towards future hydrogen networks. A focus of the project is the consideration of sequences of relaxed problems intertwined with the stochastic gradient method and a rigorous mathematical convergence analysis of the resulting methods.
We are looking for candidates with a master’s degree in mathematics or a closely related field with a strong background in optimization and partial differential equations. Prior knowledge in stochastic optimization, optimal control, or stochastic analysis is beneficial.
The appointment is limited until 30.06.2026. The reduced work schedule is 29.25 hours per week, and the salary is according to the German TVoeD Bund scale.
Please upload complete application documents including cover letter, curriculum vitae, photocopies of certificates, and transcripts as soon as possible via our online job-application facility. The advertisement is open with immediate effect and will remain open until the position is filled. We look forward to your application!
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PhD Student Position (f/m/d) (Ref. 23/14) at WIAS, Berlin, Germany Arbeitgeber: European Women in Mathematics
Kontaktperson:
European Women in Mathematics HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: PhD Student Position (f/m/d) (Ref. 23/14) at WIAS, Berlin, Germany
✨Tip Number 1
Familiarize yourself with the research group's work, especially on nonsmooth variational problems and stochastic gradient methods. This will help you articulate your interest and how your background aligns with their projects during any interviews.
✨Tip Number 2
Network with current or former PhD students from WIAS or related institutions. They can provide insights into the application process and what the research environment is like, which can be invaluable for your preparation.
✨Tip Number 3
Stay updated on recent developments in stochastic optimization and optimal control. Being knowledgeable about the latest research trends can give you an edge in discussions with the interview panel.
✨Tip Number 4
Prepare to discuss your previous research experiences and how they relate to the project on gas networks. Highlight any relevant coursework or projects that demonstrate your skills in optimization and partial differential equations.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: PhD Student Position (f/m/d) (Ref. 23/14) at WIAS, Berlin, Germany
Tipps für deine Bewerbung 🫡
Understand the Research Group: Familiarize yourself with the research group 'Nonsmooth Variational Problems and Operator Equations' and the specific project on stochastic gradient methods. This will help you tailor your application to demonstrate your interest and fit.
Craft a Strong Cover Letter: Write a compelling cover letter that highlights your academic background, relevant experience in optimization and partial differential equations, and your motivation for applying to this specific PhD position.
Prepare Your CV: Ensure your CV is up-to-date and clearly outlines your educational qualifications, research experience, and any relevant skills or projects related to stochastic optimization and optimal control.
Gather Required Documents: Collect all necessary documents including photocopies of certificates and transcripts. Make sure everything is organized and presented professionally before uploading them through the online application facility.
Wie du dich auf ein Vorstellungsgespräch bei European Women in Mathematics vorbereitest
✨Understand the Research Group
Make sure to familiarize yourself with the work of the Research Group 'Nonsmooth Variational Problems and Operator Equations'. Knowing their recent publications and ongoing projects will help you demonstrate your genuine interest and fit for the position.
✨Highlight Relevant Experience
Prepare to discuss your master's degree and any relevant experience in optimization, partial differential equations, or stochastic analysis. Be ready to provide specific examples of your work that relate to the project on stochastic gradient methods.
✨Prepare Questions
Think of insightful questions to ask during the interview. This could include inquiries about the collaborative research center TRR 154 or the specific methodologies used in the project. It shows your engagement and eagerness to learn more.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss how you approach complex mathematical problems, particularly those related to optimal control and uncertainty. Providing a clear thought process can impress the interviewers and highlight your analytical skills.
