PhD Position

PhD in Computational Condensed Matter Physics

A PhD position will open for the December 2026 intake, with applications through SRMIST’s admission cycle from September 2026. The position is described below — if it fits your interests, you are welcome to write to me ahead of the formal call. Early conversations make for stronger applications.

For what working in the group is actually like day-to-day — the tools, the culture, the temperament I look for — read the Joining MAVENs page first.

The Position

This is a computational condensed matter group working on disorder in magnetic and quantum materials — using KKR-CPA, Monte Carlo, and machine learning together to reach finite-temperature and disordered systems that any single method handles badly on its own. It is a specific methodological combination, and learning it well gives you a toolkit that transfers across problems and outlasts any particular project.

The questions are open ones. You would be expected to take a problem and drive it — formulating it, choosing the methods, deciding when a result is trustworthy. The work connects to experiment and to computational collaborators at SRMIST and CeNS, Bengaluru, so your calculations are tested against measurement rather than ending at a plot.

If you want to learn a method deeply and own a problem from question to result, that is the kind of PhD this is.

What You Would Be Working On

Open problems in magnetism, disorder, and coherence, approached with density functional theory, KKR-CPA, Monte Carlo, and machine learning. The materials are the testbed, not the subject. Current directions:

Exchange Interactions and Tc in Disordered Magnets How does chemical disorder reshape exchange pathways — and with them, the magnetic transition temperature — in metallic alloys? The goal is a validated first-principles pipeline from composition to Tc: KKR-CPA → Lichtenstein Jij → Monte Carlo. This is the group's methodology flagship and the highest-leverage project on the current plan.
Finite-Temperature Magnetism and Magnetocaloric Response In FeRh and disordered Heusler alloys, off-stoichiometry and disorder shift the metamagnetic transition and the magnetic entropy change in ways that matter for solid-state cooling. This project applies the disordered-magnetism pipeline — DLM, SOC, CPA, Monte Carlo — to predict transition temperatures and ΔSM and connect them to measurable experimental benchmarks.
Disorder-Limited Spin Coherence in Oxide Qubits Vacancies in CeO₂ produce Ce³⁺ spin centres whose coherence time T2 is limited by the surrounding disordered electron-spin bath — not the nuclear bath, which is sparse in natural Ce. This project computes the Ce³⁺ spin Hamiltonian via TB2J and propagates it through a cluster-correlation expansion to predict how vacancy concentration controls T2 and what material changes protect it. The group's highest-reach project; assigned to the strongest student after a scoping calculation.
Disorder and Catalysis in High-Entropy MXenes In doped and high-entropy MXenes, configurational disorder spreads the hydrogen adsorption energy into a distribution rather than a single value. Using special quasirandom structures and ensemble DFT, this project asks which compositions centre that distribution on the catalytic optimum — treating disorder as the design parameter, not a defect to be minimised.

The exact problem is shaped to the student over the first months.

Eligibility

  • A qualifying score in NET, GATE, or JEST is preferable and strengthens your application through the SRMIST cycle
  • A solid foundation in quantum mechanics and statistical mechanics — not just familiarity, but the ability to work with them
  • Some exposure to condensed matter physics at the MSc level
  • Evidence that you can think independently: a project, a thesis, a paper — anything where you had to figure something out without being told the answer

Marks matter less than these. A student with a strong project background and average marks is more useful to this group than the reverse.

What a PhD Here Involves

A PhD is full-time research through SRMIST, over several years. Your work is expected to reach publication quality, and co-authorship on the papers arising from it is standard — you build a real publication record, not just a thesis. Students present at workshops and conferences as the work matures, and leave with a portfolio — code, papers, and the ability to drive a problem from question to result — that holds up whether the next step is a postdoc, a research role in industry, or further academic work.

I do not promise a fixed completion timeline; a PhD takes as long as the science takes. What I do promise is that if you are working seriously, you will have my full attention and support.

How and When to Apply

The formal route is SRMIST’s PhD admission cycle, opening September 2026 for the December intake. The most useful thing you can do before then is reach out directly — an early conversation tells both of us whether there is a fit, and makes for a stronger formal application.

With me directly SRMIST admission process
Reaching out — ahead of the call
1
Write to me
Informal enquiry, ahead of the call
2
Initial conversation
If there's a fit — by email or call
SRMIST admission process
3
Applications open
September 2026
4
Entrance test & interview
Date set by SRMIST — see the SRMIST page
5
Admission offer
Following the interview
6
Session begins
December 2026

When you write, bring your CV and transcripts, your NET/GATE/JEST status if you have it, and a short note on what in the group’s work draws you in — look at the research pages and at least one recent publication first. A message that could have gone to any computational group tells me you have not thought about why this one.

I read every message. If there is a potential fit, we will talk before the formal cycle opens — and I can guide you through the departmental requirements once we are in contact.