Search by what the work actually is

Energy, Environment & Climate Materials

The division's scientific direction and its hardest materials problems.

Scale 10^-9 m to 10^6 m

Can relate an electrochemical measurement to the underlying process, and say what the measurement cannot distinguish. · Thermodynamics to the level of an energy balance over a real system. · Has analysed cycling or performance data and reported degradation rather than a best cycle. · Python for analysis of experimental or simulated energy data. + 4 more

Biology, Biotechnology & Bio-Nano Systems

Several bio-nano programmes at once, and the ethics and safety discipline across all of them.

Scale 10^-9 m to 10^-3 m

Molecular biology to the level of explaining how a measurement in an assay relates to the underlying biology. · Has analysed a real biological dataset and stated its batch effects or confounders. · Statistics for biological data: multiple testing, effect size, and why a significant result can be meaningless. · Python or R for bioinformatics, with a reproducible pipeline. + 4 more

Energy, Environment & Climate Materials

Several energy programmes at once, and the conditions-with-every-figure discipline across them.

Scale 10^-9 m to 10^6 m

Can relate an electrochemical measurement to the underlying process, and say what the measurement cannot distinguish. · Thermodynamics to the level of an energy balance over a real system. · Has analysed cycling or performance data and reported degradation rather than a best cycle. · Python for analysis of experimental or simulated energy data. + 4 more

Computer Science, AI & Scientific Computing

Property prediction and screening for the materials divisions, with false-positive rates reported.

Scale 10^-10 m to 10^-6 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

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

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

Mathematics & Computational Foundations

Numerical methods implemented, verified against their theoretical order, and handed on as reference code.

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

Models that carry the physics as a constraint, and the honest account of when that helps and when it does not.

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. + 7 more

Computer Science, AI & Scientific Computing

Machine learning on scientific data, with the evaluation designed before the model is chosen.

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. + 8 more

Materials & Advanced Matter

Two-dimensional materials, where the substrate and the edges determine most of what is measured.

Scale 10^-10 m to 10^-7 m

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. + 4 more

Materials & Advanced Matter

A scoped review of one advanced-material class, separating measured properties from computed ones.

Scale 10^-10 m to 10^0 m

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. + 4 more

Materials & Advanced Matter

What this division searches for, who searches, and the rule that a prediction is labelled a prediction.

Scale 10^-10 m to 10^0 m

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. + 4 more

Molecular Engineering & Computational Chemistry

Electronic-structure calculations that answer a question the division actually has, at a defensible level of theory.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more

Materials & Advanced Matter

The calculations: which level of theory, how convergence was tested, what the number is worth.

Scale 10^-10 m to 10^0 m

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. + 4 more

Materials & Advanced Matter

One structure-property relationship investigated computationally and checked against measured data.

Scale 10^-10 m to 10^0 m

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. + 4 more

Molecular Engineering & Computational Chemistry

The design methodology itself: how candidates are generated, screened and ranked, and how that is validated.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more

Molecular Engineering & Computational Chemistry

Designing molecules for a target property and handing on candidates a chemist could attempt to make.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more

Molecular Engineering & Computational Chemistry

What this division computes, who computes it, and the rule that a prediction is described as a prediction.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more

Materials & Advanced Matter

The division's technical direction, and the hardest problems between a computed candidate and a usable material.

Scale 10^-10 m to 10^0 m

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. + 4 more

Molecular Engineering & Computational Chemistry

The division's scientific direction and its hardest modelling problems.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more

Materials & Advanced Matter

Materials whose useful behaviour is quantum, and the calculations and measurements that establish it.

Scale 10^-10 m to 10^-8 m

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. + 4 more

Materials & Advanced Matter

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

Scale 10^-10 m to 10^0 m

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. + 4 more

Molecular Engineering & Computational Chemistry

Several design and simulation programmes at once, and the standard of theory applied across them.

Scale 10^-10 m to 10^-7 m

Can explain what a basis set is, and what changes when you change one. · Has run a geometry optimisation and can say how convergence was judged. · Understands the difference between a force field and an electronic-structure calculation, and when each is appropriate. · Thermodynamics to the level of relating a free energy difference to an equilibrium constant. + 4 more