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Extreme-Scale, Nano & Fundamental Engineering

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Individual contributor at the frontier

Senior Materials Scientist

Several materials programmes at once, and the provenance discipline applied across them.

Senior Full-Time On-site — Kolkata, West Bengal, India Permanent

Compensation

Engagement

Full-Time

Permanent role. Full-time commitment. This is an on-site role at Kolkata. It is not remote and not hybrid.

Scope of role

Own complex problems end-to-end. Set technical direction. Mentor mid and junior teammates.

Research classification

Computational Computational research Level 5 · Senior Materials & Advanced Matter →

Computing quantities that cannot be obtained in closed form, from established physics. Reproducible calculations, convergence and error budgets, released code and datasets.

Computational research. Computed from established physics. A computed number is a prediction, and it is only as good as its convergence, its error budget, and whatever data it can be checked against.

Scale range 10^-10 m to 10^0 m

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10-100 m 100 m 10100 m
Experiments reach here 3 bands no experiment reaches This role

A materials database entry computed by a high-throughput screen is a prediction, and screens are wrong at a rate that is measurable and should be reported. This division states, for every material it puts forward, whether the property was measured, computed, or inferred from a model trained on other materials. A predicted material is a candidate, not a discovery. Scientific integrity is a condition of every role in this department. Assumptions are stated separately from conclusions. Uncertainty is reported. Negative and inconclusive results are written up, not discarded. Speculative work is labelled speculative, including when that makes it less impressive. Fabrication, falsification, and presenting a simulation as a measurement end an engagement here.

Scale bands are a research classification, not a claim of experimental reach. Most of this span cannot be probed by any apparatus that exists: nothing below about 10^-19 m has been measured directly, and anything at 10^26 m or beyond is inferred from observation rather than engineered. Every opportunity states the kind of work it actually is.

01 — The role

Why this role exists at EduRankAI

Department of Extreme-Scale, Nano & Fundamental Engineering, Division D06: Materials & Advanced Matter. This division discovers and models materials, builds materials-property datasets, and develops materials for engineering use. Its computational predictions are handed on as candidates for experimental validation, and it reports which of its materials have been measured and which have only been computed. This position: Several materials programmes at once, and the provenance discipline applied across them. Scale range for this work: 10^-10 m to 10^0 m. Research classification: Computational. Computing quantities that cannot be obtained in closed form, from established physics. Evidential standing: Computational research. Computed from established physics. A computed number is a prediction, and it is only as good as its convergence, its error budget, and whatever data it can be checked against. A materials database entry computed by a high-throughput screen is a prediction, and screens are wrong at a rate that is measurable and should be reported. This division states, for every material it puts forward, whether the property was measured, computed, or inferred from a model trained on other materials. A predicted material is a candidate, not a discovery. Scale bands are a research classification, not a claim of experimental reach. Most of this span cannot be probed by any apparatus that exists: nothing below about 10^-19 m has been measured directly, and anything at 10^26 m or beyond is inferred from observation rather than engineered. Every opportunity states the kind of work it actually is. Level 5 (Senior). Several related problems at once, and the technical judgement of less experienced colleagues.

02 — The work

What you will own

  • 01 Search for materials with a target property, computationally, and rank candidates with uncertainty.
  • 02 Model materials at the level the property requires: electronic, atomistic, or continuum.
  • 03 Build and curate materials-property datasets, with provenance recorded per entry.
  • 04 Develop materials toward an engineering application in another division, with the requirement stated first.
  • 05 Support experimental validation and report the cases where measurement disagreed with prediction.
  • 06 Relate structure to property to performance, and say where the chain of inference weakens.
  • 07 Carry several related problems at once without losing the thread of any of them.
  • 08 Raise the technical judgement of less experienced colleagues, in review and in person.

03 — The expertise

What we look for

Can relate a crystal structure to at least one measurable property and explain the mechanism.Reads a phase diagram and can say what happens on cooling through a boundary.Has analysed real characterisation data — diffraction, microscopy or mechanical testing — and stated its uncertainty.Python for data analysis over a materials dataset.Reports whether a property was measured or computed, every time.PythonC++Scientific computing

04 — The bar

Who thrives here

  • Education: Doctorate or an equivalent research record.
  • Experience: 6 to 10 years, including work that other people have built on.
  • Scope of the role: Several related problems at once, and the technical judgement of less experienced colleagues.
  • Must have: Can relate a crystal structure to at least one measurable property and explain the mechanism. Also: Reads a phase diagram and can say what happens on cooling through a boundary.
  • Portfolio: at least one piece of work — code, a written result, a thesis chapter, a preprint — that somebody outside your institution can read and assess. It does not need to be published.

Terms of Engagement

How working time works at this level

No counted hours. A five-day week with a four-hour overlap window so colleagues can reach you, and objectives agreed for the cycle.

Type

Senior

Working days

5 per week

Rest days

2 per week

Hours counted

No

Daily overlap

4h

Measured by

Objectives agreed for the cycle, the quality of the judgement calls, and the people the work makes better. Not attendance.

Where this stands legally

Hours are not counted at this level. The statutory ceiling of 9 hours a day and 48 a week remains the limit the role is designed to fit inside: if the work cannot be done within a normal week, the scope is wrong, not the person.

The full per-level model is published at Working Hours by Level.

05 — Hiring process

What to expect after you apply

  1. 01

    Application review

    Every application is read personally within five business days. We respond either way.

  2. 02

    Take-home or live exercise

    Role-specific. Time-boxed. Real problems we are actually working on, not invented puzzles.

  3. 03

    Conversations

    Deep technical and values conversations with the team you would join. No trick questions. No panel ambushes.

  4. 04

    Offer or honest no

    If yes: digital offer letter, signed in-portal, transparent terms. If no: written feedback if you want it.

The standard

What you deliver, and how it is judged

Deliverables

  • Candidate materials with computed properties, uncertainty, and the method used.
  • Datasets with per-entry provenance: measured, computed, or model-inferred.
  • Validation reports including disagreements between prediction and measurement.
  • Structure-property-performance write-ups that name the weakest link in the chain.

Evaluation criteria

  • Whether provenance is recorded for every property.
  • Whether the model was tested on held-out data rather than on what it was fitted to.
  • Honesty about screening false-positive rates.
  • Usefulness of the output to the engineering division that asked for it.

Preferred, not required

Nothing in this list is a bar to applying.

Thermodynamics and kinetics of phase transformations.Experience with an electronic-structure or atomistic simulation package.Statistics sufficient to avoid over-reading a small sample.Familiarity with an open materials database and its known limitations.Machine learning applied to materials property prediction, with a held-out test set.Hands-on mechanical testing or metallography.Experience with a high-throughput screening pipeline.

Tools you would work in

DFT packagesPymatgen or an equivalent materials toolkitThermodynamic modelling softwareScikit-learn or PyTorch for property modelsData pipelinesGit

Reports to: Materials & Advanced Matter Lead

Works with: D04, D05, D07, D10, D11, D13, D14

Before you start

What we will collect. What it costs. What we will not do with it.

We will collect

  • Name, email, phone — Account + application updates. No marketing.
  • Resume / portfolio link — Human review of your work.
  • Date + place of birth — Identity verification only.
  • Your written responses — Selection rubric. Read by humans.
  • Government ID (later) — Anti-fraud at offer / interview stage. Not at signup.

We will never

  • Sell your data
  • Share with third-party recruiters
  • Use for advertising
  • Train models on it
  • Send marketing email

Our situation

EduRankAI is a small, independent organization building long-term capabilities in educational intelligence, advanced AI systems, and research infrastructure. We take no advertiser money, no donations with strings attached, and no investor pressure on hiring decisions. Applying is free, and every application is read by a human — recruitment, technical, academic and leadership teams. It buys us the right to be honest.

Full transparency policy Questions? Email us

Ready to apply?

We read every application personally. If you are the right person for this role — regardless of pedigree, background, or where you are based — you will hear back from us within five business days.

Apply through this page. You will be asked for your education, your experience, and links to work we can actually read — a repository, a write-up, a thesis chapter, a preprint. Send the piece of work you would defend, not the one with the best title. If a result in it turned out to be wrong, say so; we would rather read that than not know. Every application is read by a person. We assess applications on evidence of the work. We do not filter on institution, on age, on gender, on caste, on religion, on disability, or on where you are from. If any part of this process is inaccessible to you, tell us and we will change it for you.

Senior Full-Time

Senior Materials Scientist

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