Search by what the work actually is

Computer Science, AI & Scientific Computing

What this division builds for the others, who builds it, and the rule that no model ships without its baseline.

Scale 10^-100 m to 10^100 m

Fluent in Python, and able to write code somebody else can read, test and extend. · Data structures and algorithms to the level of choosing correctly and justifying the choice. · Comfortable on Linux, and with Git as a working tool rather than a save button. · Has written tests for numerical code and can explain what a tolerance in a test means. + 6 more

Aerospace, Space & Extreme Environment Engineering

Aerospace systems analysed and designed against requirements with traceable margins.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

A cosmological calculation carried out and compared against published constraints.

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Aerospace, Space & Extreme Environment Engineering

The division's technical direction and its hardest system-level problems.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Aerospace, Space & Extreme Environment Engineering

Several aerospace programmes at once, and the margin discipline applied across them.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Astrophysics, Cosmology & Extreme-Scale Modelling

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

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

Aerospace, Space & Extreme Environment Engineering

What this division works on, who works on it, and the rule that maturity is stated in every outward claim.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Aerospace, Space & Extreme Environment Engineering

Whole spacecraft systems: budgets, interfaces, and the subsystem that ends up driving everything.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 5 more

Aerospace, Space & Extreme Environment Engineering

One aerospace analysis carried out under real constraints that trade against each other.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Aerospace, Space & Extreme Environment Engineering

A mission concept analysed to first-order budgets, with the binding constraint identified.

Scale 10^3 m to 10^13 m

Orbital mechanics: can propagate a two-body orbit and explain what perturbs it. · Has run an engineering analysis for a system with mass, power and thermal constraints that trade against each other. · Understands the space environment: vacuum, radiation, thermal cycling, and what each does to hardware. · Python for mission and systems analysis. + 4 more

Computer Science, AI & Scientific Computing

A scientific prediction task with a proper held-out split and a classical baseline reported beside the model.

Scale 10^-100 m to 10^100 m

Fluent in Python, and able to write code somebody else can read, test and extend. · Data structures and algorithms to the level of choosing correctly and justifying the choice. · Comfortable on Linux, and with Git as a working tool rather than a save button. · Has written tests for numerical code and can explain what a tolerance in a test means. + 6 more

Mathematics & Computational Foundations

Whole modelling problems from other divisions: formulation, analysis, and an honest statement of validity.

Scale 10^-100 m to 10^100 m

Can state and use the definition of convergence for a numerical scheme, not just cite the order. · Linear algebra to the level of conditioning, decompositions and why an ill-conditioned problem is not a bug in the solver. · Real analysis: limits, continuity, and what makes a problem well-posed. · Has implemented a numerical method from a paper and verified its convergence order empirically. + 5 more

Mathematics & Computational Foundations

A modelling question from another division formulated mathematically and checked for well-posedness.

Scale 10^-100 m to 10^100 m

Can state and use the definition of convergence for a numerical scheme, not just cite the order. · Linear algebra to the level of conditioning, decompositions and why an ill-conditioned problem is not a bug in the solver. · Real analysis: limits, continuity, and what makes a problem well-posed. · Has implemented a numerical method from a paper and verified its convergence order empirically. + 5 more

Computer Science, AI & Scientific Computing

The computation another division needs, made correct, fast enough, and reproducible.

Scale 10^-100 m to 10^100 m

Fluent in Python, and able to write code somebody else can read, test and extend. · Data structures and algorithms to the level of choosing correctly and justifying the choice. · Comfortable on Linux, and with Git as a working tool rather than a save button. · Has written tests for numerical code and can explain what a tolerance in a test means. + 6 more

Mathematics & Computational Foundations

Where the mathematics and the machine meet: conditioning, floating point, and what the computed answer is worth.

Scale 10^-100 m to 10^100 m

Can state and use the definition of convergence for a numerical scheme, not just cite the order. · Linear algebra to the level of conditioning, decompositions and why an ill-conditioned problem is not a bug in the solver. · Real analysis: limits, continuity, and what makes a problem well-posed. · Has implemented a numerical method from a paper and verified its convergence order empirically. + 5 more

Computer Science, AI & Scientific Computing

Making the department's workloads run at scale, with measured scaling curves rather than claims.

Scale 10^-100 m to 10^100 m

Fluent in Python, and able to write code somebody else can read, test and extend. · Data structures and algorithms to the level of choosing correctly and justifying the choice. · Comfortable on Linux, and with Git as a working tool rather than a save button. · Has written tests for numerical code and can explain what a tolerance in a test means. + 9 more