Departments / Extreme-Scale, Nano & Fundamental Engineering / D15

Astrophysics, Cosmology & Extreme-Scale Modelling

Computational astrophysics and cosmology: observational data analysis, gravitational and structure modelling, large-scale simulation, and the mathematics of models at and beyond the observable horizon.

Computational Computational research 10^13 m to 10^100 m 10 open

What this work is, and what it is not

Nothing at this scale is engineered and nothing is experimented on. The observable universe has a radius of roughly 10^26 m; everything beyond that is a property of a cosmological model rather than an observation, and this division says so every time it publishes a figure that extends past it. Simulation output is a model realisation, not data, and is labelled as such in every figure it appears in.

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.

Part of this division's range sits where no experiment reaches: Cosmological, theoretical and computational. Work in those bands is theory and computation, and every posting says which side of that line it falls on.

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.

Where this division sits

Scale range 10^13 m to 10^100 m

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10^-100 m 10⁰ m 10¹⁰⁰ m

Experiments reach here 3 bands no experiment reaches This role

B10

Stellar and galactic modelling (10^13 to 10^26)
Stars, star systems, galaxies and large-scale structure. Observed remotely and modelled computationally. Nothing at this scale is engineered.

B11

Cosmological, theoretical and computational (10^26 to 10^100)
At and beyond the edge of the observable universe. A statement about this band is a statement about a cosmological model, not about anything that can be observed.

Charter

This division analyses observational and public datasets, develops cosmological models, runs simulations, quantifies uncertainty, and compares models against observations. It distinguishes evidence, inference and speculation in every result, because at this scale those three are easy to confuse and expensive to confuse.

Domains

AstrophysicsComputational astrophysicsCosmologyGravitational modellingLarge-scale structureStellar systemsGalactic modellingUniverse-scale simulationMathematical cosmology

Disciplines

Astrophysics Cosmology Physics Mathematics Scientific computing

Works with

Divisions this one collaborates with routinely.

D01D02D08D09D14

10 open opportunities

Grouped by career rung. Every posting states its own classification, its scale range and what it expects you to have already done.

Level 1 3

Astrophysics Research Intern

One astrophysical question answered from public survey data, selection function included.

Computational Computational research L1 · Research and Engineering Intern Internship On-site / Hybrid — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Computational Astrophysics Intern

A small simulation run at two resolutions, with the convergence difference reported.

Simulation Computational research L1 · Research and Engineering Intern Internship On-site / Hybrid — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Cosmology Intern

A cosmological calculation carried out and compared against published constraints.

Theoretical Theoretical research L1 · Research and Engineering Intern Internship On-site / Hybrid — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Level 3 4

Astrophysics Data Engineer

The pipelines survey data flows through, and the provenance that lets a figure be traced to a run.

Computational Computational research L3 · Engineer and Scientist Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 7 more

Astrophysics Research Scientist

Astrophysical systems modelled and compared against observation, at scales that are observed.

Computational Computational research L3 · Engineer and Scientist Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Computational Cosmologist

Cosmological simulation and inference, with convergence and systematics treated as first-class.

Computational Computational research L3 · Engineer and Scientist Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Cosmology Research Scientist

Cosmological models and their confrontation with data, including where the model is under-determined.

Theoretical Theoretical research L3 · Engineer and Scientist Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Level 5 1

Senior Computational Astrophysicist

Several simulation and analysis programmes at once, and the convergence discipline across them.

Computational Computational research L5 · Senior Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Level 6 1

Cosmology & Extreme-Scale Lead

What this division works on, who works on it, and the rule that beyond the observable horizon we describe a model, not the universe.

Computational Computational research L6 · Lead Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Level 7 1

Principal Cosmologist

The division's scientific direction and the questions where inference and speculation are hardest to separate.

Computational Computational research L7 · Principal Full-Time On-site — Kolkata, West Bengal, India

Scale 10^13 m to 10^100 m

Can explain what a redshift measures and what has to be assumed to turn it into a distance. · Has analysed a real astronomical dataset, including its selection function. · Statistics and Bayesian inference: priors, posteriors, and what a credible interval claims. · Python for astronomical data analysis, in a pipeline that reruns. + 5 more

Other divisions in this department

Ultra-Fundamental & Mathematical Physics Particle, High-Energy & Nuclear Systems Quantum, Atomic & Precision Systems Molecular Engineering & Computational Chemistry Nano Engineering & Nanotechnology Materials & Advanced Matter Semiconductors, Electronics & Micro/Nano Systems Computer Science, AI & Scientific Computing Mathematics & Computational Foundations Mechanical, Robotics & Multi-Scale Systems Civil, Structural & Macro-Scale Systems Biology, Biotechnology & Bio-Nano Systems Energy, Environment & Climate Materials Aerospace, Space & Extreme Environment Engineering