Open to opportunities

anjali singh

@anjalisingh19

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Scientific machine learning researcher applying deep learning to PDEs.

India

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What I'm looking for

I’m looking for a research-focused role in scientific machine learning, where I can build and validate deep learning methods for nonlinear PDEs and phase-field models. I want a team that values rigorous numerical analysis and strong experimentation.

I’m a Ph.D. scholar in Mathematics at IIT Guwahati, focused on “Numerical Analysis of Deep Learning Methods for the Allen-Cahn and Cahn-Hilliard Models.” My work blends scientific machine learning with rigorous numerical thinking to tackle phase-field models and nonlinear PDEs through neural network-based solution frameworks.

Through my Ph.D. and publications, I’ve developed and evaluated deep learning methods such as “Mc-DSOSLS,” “Mc-PINN,” and hybrid Strang-splitting deep neural networks for the Allen-Cahn and Cahn-Hilliard equations, including phase-field formulations. I’m especially motivated by neural approaches that are both accurate and computationally efficient, and I bring strong teaching experience as a Teaching Assistant across mathematics and scientific computing courses.

Experience

Work history, roles, and key accomplishments

PhD Researcher in Mathematics

Indian Institute of Technology Guwahati

Jan 2020 - May 2026 (6 years 4 months)

Developed deep learning numerical methods for Allen-Cahn and Cahn-Hilliard phase-field PDEs, using hybrid least-squares and conservative approaches. Published 4 journal papers and has additional work under review with focus on evolving-surface formulations and sampling-based training.

Deep Learning PyTorch Python Least Squares Methods (FOSLS SOSLS)Phase Field Modeling Allen Cahn & Cahn Hilliard PDEs Metropolis Hastings Sampling Strang Splitting

Education

Degrees, certifications, and relevant coursework

Indian Institute of Technology Guwahati

Doctor of Philosophy (PhD) in Mathematics, Mathematics

2020 - 2025

Activities and societies: Supervisor: Prof. Rajen Kumar Sinha.

Ph.D. in Mathematics at IIT Guwahati (2020–2025). Thesis: Numerical Analysis of Deep Learning Methods for the Allen-Cahn and Cahn-Hilliard Models; defended on 19 May 2026 under Prof. Rajen Kumar Sinha.