CompFlowLab@Monash currently has two open PhD positions. Interested candidates should send a cover letter detailing their interest in joining the lab, along with their curriculum vitae, to rishabh.more@monash.edu.

Join CompFlowLab at Monash University!

Fluid mechanics and the rheology of soft matter are essential for understanding how materials flow, deform, and self-organize—insights that underpin modern manufacturing. At some stage in its production, nearly every product, from advanced materials to everyday items, exists in a soft matter state. By studying and controlling these behaviors, we can innovate across industries such as advanced manufacturing, sustainability, renewable energy, food processing, and mining.

Our lab at Monash University leads in this dynamic field, blending experimental, theoretical, and data-driven approaches to solve real-world challenges. With cutting-edge facilities, strong industry collaborations, and an interdisciplinary research environment, we empower our researchers to innovate and make a global impact.

Why Join Us?

• Impactful Research: Address global sustainability, energy, and industrial efficiency challenges.

• Interdisciplinary Opportunities: Collaborate across chemical engineering, mechanical engineering, physics, mathematics, and related fields.

• Career Advancement: Gain expertise to excel in academia, industry, or entrepreneurship.

Interested scientists and engineers from various disciplines are welcome to get in touch. CompFlowLab@Monash trains postgraduate students (PhD and Masters) and project students (e.g., Bachelor) in Chemical Engineering, Mechanical Engineering, Physics, Mathematics, and related fields.

Masters by Research or PhD Scholarships in Chemical Engineering are open for applications:

• Domestic students: Until the end of May and October.

• International students: Until the end of March and August.

More information about these opportunities can be found here.

Current PhD Research Projects:

1. Efficient Liquid Coolants Using Elastoinertial Instabilities in Dilute Polymeric Solutions

• Design innovative liquid coolants by leveraging elastoinertial instabilities and elastic turbulence in dilute polymeric solutions.
• Enhance convective heat transfer efficiency while minimizing energy consumption with applications in high-performance electronics cooling and thermal management of electric vehicle batteries.
• Combine experimental fluid dynamics, advanced rheological measurements, and computational modeling to optimize coolant formulations.

2. Exploring Extensional Rheology Using a Filament Stretching Rheometer

• Investigate the extensional flow properties of polymer solutions, emulsions, and other complex fluids using a filament stretching rheometer.

• Study behaviors such as strain hardening, filament breakup, and relaxation to improve material design for applications in fiber spinning, 3D printing, and coating technologies.

• Incorporate machine learning techniques to automate data analysis and uncover new correlations between rheological properties and performance in manufacturing processes.

3. Flow-and-Field-Induced Self-Organization in Colloidal Suspensions for Designing Functional Materials

• Investigate the multiscale physics of flow- and field-induced self-organization in colloidal suspensions, such as creating particle-rich stripes in confined flows.

• Apply findings to the design of flexible electronics, 3D printing inks, advanced flow batteries, and anisotropic conductive composites.

• Use theory, coarse-grained simulations, and data-driven predictive models to push the boundaries of soft matter mechanics.

4. AI-Driven Fluid Dynamics for Sustainable Manufacturing

• Utilize machine learning to model and optimize fluid flow in industrial processes, enhancing energy efficiency and reducing waste.

• Focus on sustainable manufacturing and renewable energy applications, such as wind turbine optimization and hydropower.

• Collaborate with industry to integrate predictive algorithms into real-world workflows.

5. Rheology of Soft Matter in Food and Mining Industries

• Study the viscoelastic properties of emulsions, gels, and slurries to improve product stability and consistency in food processing.

• Optimize slurry flow behaviors in mining for efficient transport and reduced environmental impact.

• Combine advanced imaging techniques and computational models to link microstructural dynamics to macroscopic performance.