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Numerical Simulation of Biological Interfaces and Elastic Surfaces in Fluid Flows

Freiberg University of Mining and Technology Institute of Numerical Mathematics and Optimization
✓ Fully Funded 🎓 Computational Mathematics 🎓 Engineering Mathematics 🎓 Environmental Sciences numerical simulation computational physics fluid dynamics biological interfaces elastic surfaces finite element method mathematical modeling

Explore the development of mathematical models and simulations of biological interfaces interacting with fluids. Develop and implement finite element codes to study elastic surfaces in fluid flows, gaining insights into fundamental biological processes.

AI-generated overview

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Why This Research Matters

This research advances understanding of biological processes by modeling the fluid-elastic interface interactions fundamental to cellular mechanics and other life sciences. The outcomes contribute to improved biophysical insights, enabling experimental validations and influencing developments in biomedical engineering and computational physics.

Numerical Simulation of Surfaces and Evolving Geometries Scientific Computing Cells and Membranes

Project Description

Project Overview

The group of numerical mathematics at TU Freiberg, led by Prof. Dr. Sebastian Aland, focuses on developing mathematical models for the complex interactions between fluids and elastic materials. This project, in cooperation with HTW Dresden, aims to enhance understanding of biological processes by simulating elastic surfaces in fluid flows through advanced numerical methods.

What You Will Do

  • Develop new mathematical models to simulate biological interfaces such as membranes and fluidic surfaces.
  • Implement and discretize these models using finite element methods.
  • Perform numerical simulation studies in collaboration with experimental partners to investigate fundamental biophysical phenomena.

Expected Outcomes

Generation of robust mathematical frameworks and numerical algorithms to better understand the role of elastic surfaces in biology. Insights gained will advance knowledge in biophysics and contribute to the broader computational mathematics community.

Why This Matters

Understanding the interplay between fluid flow and elastic biological interfaces is key to uncovering fundamental life principles. These simulations help bridge theory and experiment, enabling novel insights into cellular mechanics and other biological processes with important implications for medicine and bioengineering.

Entry Requirements

Diploma or master’s degree in Mathematics, Computational Engineering Science, Physics, or related field with highly competitive grades. Strong knowledge of numerical discretization of differential equations and advanced programming skills are required. Ability to work in teams and strong communication skills are expected.

How to Apply

Apply via https://alandlab.de/group/sebastian-aland/ or contact the research group directly.

Eligibility

UK/Home
EU
International

Supervisor Profile

PD
Prof. Dr. Sebastian Aland
Freiberg University of Mining and Technology, Institute of Numerical Mathematics and Optimization
2616 Citations
25 h-index
Google Scholar

Prof. Dr. Sebastian Aland is a leading researcher at TU Freiberg and HTW Dresden specializing in numerical simulation of surfaces and evolving geometries, combining expertise in numerical mathematics, scientific computing, and biophysical applications. His research integrates high-performance computing with mathematical modeling to understand fluid-elastic material interactions, contributing influential work recognized internationally with over 2600 citations and a solid h-index of 25.

Key Publications

2015 328 citations
Extracting Cell Stiffness from Real-Time Deformability Cytometry: Theory and Experiment
2013 311 citations
Wetting resistance at its topographical limit: the benefit of mushroom and serif T structures
2012 225 citations
Benchmark computations of diffuse interface models for two‐dimensional bubble dynamics
2017 173 citations
Numerical simulation of real-time deformability cytometry to extract cell mechanical properties
2013 131 citations
Tunable nano-replication to explore the omniphobic characteristics of springtail skin

Research Contributions

Advanced numerical simulations for real-time deformability cytometry allow extraction of cell mechanical properties.
Enables better understanding of biomechanical cell characteristics important for medical diagnostics.
Developed benchmark computations for diffuse interface models in two-dimensional bubble dynamics.
Improves computational fluid dynamics accuracy applicable in engineering and scientific simulations.
Explored surface topographies such as mushroom and serif T structures to enhance wetting resistance.
Provides insights for developing advanced water-repellent and self-cleaning materials.

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