PhD Position Analysis of Partial Differential Equations
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Описание вакансии
TL;DR
PhD Position (PDE Analysis): Investigating qualitative and quantitative aspects of PDEs from structured population dynamics and kinetic theory with an accent on well-posedness, long-term behavior, scaling limits, and information-theoretical approaches. Focus on employing tools from PDE theory, functional analysis, and probability theory to analyze kinetic equations like Boltzmann and Landau equations.
Location: Onsite in Delft, Netherlands. Relocation support to the Netherlands available.
Salary: €3059–€3881 gross per month (increasing yearly), plus holiday allowance and end-of-year bonus.
Company
Delft University of Technology () is a top international university combining science, engineering, and design to address global challenges.
What you will do
- Analyze PDEs from population dynamics and kinetic theory using mathematical tools.
- Investigate well-posedness, long-term behavior, scaling limits, and applications of information theory.
- Present research at national and international conferences with travel budget support.
- Engage in a light teaching load and learn new techniques to broaden mathematical background.
Requirements
- Master's degree in mathematics or related discipline (or soon to obtain).
- Profound knowledge of PDE analysis and preferably probability theory.
- Excellent English proficiency (written and spoken).
- Eagerness to tackle complex mathematical challenges.
- Ability to work independently and collaboratively.
Culture & Benefits
- 4-year contract (initial 1.5 years, then 2.5 years after assessment).
- Enrollment in Graduate School with skills training.
- Customizable compensation package, health insurance discounts, work costs contribution.
- Flexible work schedules and support for international relocation including dual career program.
- Diversity and inclusion focus with vibrant international community.
Hiring process
- Apply by 30 June 2026 with CV, motivation letter, transcripts, publications (if any), theses.
- Online interview with supervisor if shortlisted.
- Knowledge security risk assessment at final stages.
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