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Patrick Huber

1 month ago

Fully Funded PhD in Transport Processes in Nanoporous Hybrid Materials at Technische Universität Hamburg Technische Universität Hamburg in Germany

I am sharing a fully funded PhD position in transport processes in nanoporous hybrid materials at Technische Universität Hamburg.

Technische Universität Hamburg

Germany

Expired

Description

The Institute of Geo-Hydroinformatics at Technische Universität Hamburg (TUHH) is offering a fully funded PhD position focused on 'Transport Processes in Nanoporous Hybrid Materials.' The successful candidate will join the BlueMat Cluster of Excellence and work under the co-supervision of Prof. Patrick Huber (TUHH) and Dr. Sahar Bakhshian (Rice University). The research aims to develop multiscale modelling tools to understand and predict fluid transport in nanoporous hybrid materials, with the goal of linking pore-scale information to continuum-scale behavior. This work will support the design of smart nanoporous materials for industrial and environmental applications. The project combines Lattice Boltzmann simulations, machine learning, and continuum-scale modelling to bridge scales and deliver predictive insights. Candidates should have a strong background in porous media flow, computational fluid dynamics, or machine learning, and be eager to work in a collaborative, international research environment. The position is fully funded until January 2029 and offers access to top-tier training and networking opportunities through the BlueMat Academy. Applications are open until December 28, 2024. For more information and to apply, visit the TUHH job portal.

Funding

The position is fully funded until January 2029. It is a full-time PhD position with salary and benefits according to German university standards. Funding includes stipend and access to training and networking opportunities through the BlueMat Academy.

How to apply

Apply via the provided application link to the TUHH job portal. Prepare your CV and supporting documents. Follow the instructions on the official job posting. Contact the supervisors for further information if needed.

Requirements

Applicants should have a strong background in porous media flow, computational fluid dynamics, or machine learning. A relevant degree in engineering, physics, materials science, or a related field is expected. Experience with multiscale modelling tools and simulations is desirable. Good communication skills and the ability to work in an international, collaborative environment are important.

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