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Extreme-Scale, Nano & Fundamental Engineering

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Senior leadership

High-Energy Physics Lead

What this division analyses, who analyses it, and how uncertainty is reported before anything is published.

Lead 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

Set direction within your domain. Build and mentor a team. Own outcomes at the function level.

Research classification

Computational Computational research Level 6 · Lead Particle, High-Energy & Nuclear Systems →

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^-18 m to 10^-12 m

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

This is the smallest scale anything has actually been measured at, and the measurement is statistical. Results here are distributions with uncertainties, not single numbers, and a result quoted without its uncertainty is not a result. We analyse public and collaboration datasets; we do not operate accelerator facilities and do not claim to. 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 D02: Particle, High-Energy & Nuclear Systems. This division works where theory meets very large datasets. It builds simulation pipelines, analyses public and collaboration datasets, quantifies uncertainty honestly, and supports detector and materials research with computation. It does not operate an accelerator. This position: What this division analyses, who analyses it, and how uncertainty is reported before anything is published. Scale range for this work: 10^-18 m to 10^-12 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. This is the smallest scale anything has actually been measured at, and the measurement is statistical. Results here are distributions with uncertainties, not single numbers, and a result quoted without its uncertainty is not a result. We analyse public and collaboration datasets; we do not operate accelerator facilities and do not claim to. 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 6 (Lead). A research programme or an engineering area: what gets worked on, by whom, and to what standard.

02 — The work

What you will own

  • 01 Model particle and nuclear interactions and compare the models against measured distributions.
  • 02 Analyse public and collaboration datasets, with the selection criteria written down before the result is looked at.
  • 03 Build and maintain simulation pipelines that run reproducibly at scale.
  • 04 Quantify statistical and systematic uncertainty separately, and report both.
  • 05 Validate computational results against known cases before trusting them on unknown ones.
  • 06 Support detector and radiation-damage research with modelling other divisions can use.
  • 07 Decide what this area works on, who works on it, and the standard the work is held to.
  • 08 Be accountable for the honesty of what leaves the division, including under time pressure.
  • 09 Recruit, develop and retain the people the programme needs.

03 — The expertise

What we look for

Can state what a cross-section is, in what units, and how it relates to an event rate.Has written a Monte Carlo simulation and can explain its variance and how it was reduced.Competent in statistics: likelihood, confidence intervals, and why a p-value is not a probability that a hypothesis is true.Can write analysis code in Python or C++ that another person can run on the same data and reproduce.Reports uncertainty with every number, and separates statistical from systematic.PythonC++Scientific computing

04 — The bar

Who thrives here

  • Education: Doctorate or an equivalent research record.
  • Experience: 8 to 12 years, with a record of directing work carried out by other people.
  • Scope of the role: A research programme or an engineering area: what gets worked on, by whom, and to what standard.
  • Must have: Can state what a cross-section is, in what units, and how it relates to an event rate. Also: Has written a Monte Carlo simulation and can explain its variance and how it was reduced.
  • 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, plus responsibility for the coverage of your area — including who is on call and when.

Type

Lead

Working days

5 per week

Rest days

2 per week

Hours counted

No

Daily overlap

4h

Measured by

The outcomes of the area you lead, the reliability of its coverage, and the growth of the people in it.

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

  • Analysis code with a fixed environment, a recorded selection, and a seeded run.
  • Distributions and fits reported with statistical and systematic uncertainties separated.
  • Validation notes showing the pipeline reproducing a known result before it was used on a new one.
  • Simulation configurations another division can run without asking how.

Evaluation criteria

  • Whether the uncertainty budget is complete and defensible.
  • Reproducibility of the analysis from a clean checkout.
  • Validation against a known benchmark before any novel claim.
  • Resistance to the temptation to tune a selection after seeing the result.

Preferred, not required

Nothing in this list is a bar to applying.

A graduate course in quantum field theory or nuclear physics.Experience with a large dataset that did not fit in memory.Familiarity with at least one detector simulation or event-generation toolkit.Version-controlled analysis with a recorded environment.Experience on an experimental collaboration, at any level.HPC or batch-scheduler experience.Machine learning applied to physics data, with an honest classical baseline alongside it.

Tools you would work in

ROOT or an equivalent analysis frameworkGeant4-style detector simulationNumPy and SciPyHPC batch schedulersGitContainerised environments

Reports to: Department Director

Works with: D01, D06, D08, D09

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.

Lead Full-Time

High-Energy Physics Lead

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