Departments / Extreme-Scale, Nano & Fundamental Engineering / D13

Energy, Environment & Climate Materials

Battery and energy-storage materials, hydrogen systems, solar materials, catalysis, carbon capture, water purification, environmental nanotechnology and climate systems modelling.

Computational Computational research 10^-9 m to 10^6 m 11 open

What this work is, and what it is not

An energy material's headline number is meaningless without its conditions: a capacity at what rate, over how many cycles, at what temperature; an efficiency under what spectrum and what area. This division states conditions with every figure, reports cycle-life degradation rather than first-cycle performance, and does not describe a laboratory-scale result as a deployable technology.

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 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^-9 m to 10^6 m

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10^-100 m 10⁰ m 10¹⁰⁰ m

Experiments reach here 3 bands no experiment reaches This role

B05

Nano (10^-9 to 10^-6)
Molecules, nanostructures, two-dimensional materials and quantum dots. Fabricated, imaged and characterised routinely.

B06

Micro (10^-6 to 10^-3)
Microelectronics, MEMS, microfluidics and cellular biology. Mature fabrication and metrology.

B07

Meso and human-scale devices (10^-3 to 10^0)
Components, instruments and devices a person can hold. Where most engineering prototypes are built and tested.

B08

Macro, infrastructure and planetary surface (10^0 to 10^6)
Machines, structures, vehicles, buildings and infrastructure networks, up to regional scale.

Charter

This division develops materials concepts for energy and environmental problems, models energy systems, analyses environmental impact, and builds computational discovery workflows. Every performance claim is stated with the conditions it was obtained under, because energy claims without conditions are how this field acquired its credibility problem.

Domains

Battery materialsHydrogen systemsSolar materialsCatalysisCarbon capture materialsWater purificationEnvironmental nanotechnologyEnergy storageClimate systems modelling

Disciplines

Energy Environment and climate Materials science Chemistry Scientific computing

Works with

Divisions this one collaborates with routinely.

D04D05D06D08D11D12

11 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

Battery Materials Intern

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

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

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

Climate Materials Intern

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

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

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 Research Intern

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

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

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

Level 3 4

Battery Engineer

Cells and their real behaviour over life, including the failure mode that ends them.

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

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. + 5 more

Catalyst Engineer

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

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

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 Materials Engineer

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

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

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

Environmental Nano Engineer

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

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

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

Level 4 1

Computational Energy Scientist

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

Computational Computational research L4 · Specialist Full-Time On-site — Kolkata, West Bengal, India

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

Level 5 1

Senior Energy Engineer

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

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

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

Level 6 1

Energy & Climate Lead

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

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

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

Level 7 1

Principal Energy Materials Scientist

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

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

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

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 Aerospace, Space & Extreme Environment Engineering Astrophysics, Cosmology & Extreme-Scale Modelling