Search by what the work actually is

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

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

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

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

Energy, Environment & Climate Materials

Cycling data analysed for degradation, reporting the trend rather than the best cycle.

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

Nanoscale structures that have to work in contact with living material, and what that constrains.

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

Biology, Biotechnology & Bio-Nano Systems

One bio-nano interface studied computationally, with what the model leaves out written down.

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

Biology, Biotechnology & Bio-Nano Systems

What this division works on, who works on it, and the rule that approvals come before work.

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

Biology, Biotechnology & Bio-Nano Systems

The pipelines and the statistics the division's biological conclusions rest on.

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. + 5 more

Biology, Biotechnology & Bio-Nano Systems

Materials meant for biological contact: response, degradation, and the failure the material eventually has.

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

Biology, Biotechnology & Bio-Nano Systems

A scoped biotechnology question worked through with its biosafety and ethics context stated.

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

Catalysts modelled and assessed, including deactivation rather than initial activity alone.

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. + 6 more

Energy, Environment & Climate Materials

A material for a climate application assessed against a stated environmental requirement.

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

Biological questions answered computationally, with confounders addressed rather than mentioned.

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

Biology, Biotechnology & Bio-Nano Systems

A public biological dataset analysed end to end in a pipeline that reruns from raw data.

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

The modelling the division's energy claims rest on, and the honest accounting of losses.

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

Energy, Environment & Climate Materials

What this division works on, who works on it, and the rule that a laboratory result is not a deployable technology.

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

Energy, Environment & Climate Materials

Materials for energy applications, developed against a requirement and reported with conditions.

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

Energy, Environment & Climate Materials

One energy material or system analysed with its performance conditions stated throughout.

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

Energy, Environment & Climate Materials

Nanomaterials for environmental use, and the question of what happens to them afterwards.

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

The division's scientific direction and the hardest problems at the biology-engineering boundary.

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