Careers · Research opportunities

Search by what the work actually is

Every research posting carries a classification and a scale range. Filter by either, and by division, discipline, career rung or how recently it was posted. Everything you choose is kept in the address bar, so a search can be shared or bookmarked.

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.

Browse by scale band

Eleven bands from 10-100 m to 10100 m. Click one to filter. The hatched bands are the ones no apparatus reaches.

10-100 m 100 m 10100 m
Experiments reach here 3 bands no experiment reaches
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58 opportunities match your filters

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Nano Engineering Lead

Nano Engineering & Nanotechnology

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

Applied engineering Established science L6 · Lead Full-Time On-site — Kolkata, West Bengal, India

Scale 10^-9 m to 10^-6 m

Can explain why a property changes when a material is made small, in terms of surface-to-volume ratio or quantum confinement. · Has interpreted characterisation data — microscopy, diffraction or spectroscopy — and can state what the technique cannot tell you. · Materials science to the level of relating structure to a measurable property. · Can carry out and document a calculation or an analysis in Python that somebody else can rerun. + 4 more

Battery Engineer

Energy, Environment & Climate Materials

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

Battery Materials Intern

Energy, Environment & Climate Materials

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

Bio-Nano Engineer

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Bio-Nano Research Intern

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Bio-Nano Systems Lead

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Bioinformatics Scientist

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Biomaterials Engineer

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Biosensor Engineer

Biology, Biotechnology & Bio-Nano Systems

Sensing concepts developed to a limit of detection derived in a realistic sample matrix.

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

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

Biotechnology Intern

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Catalyst Engineer

Energy, Environment & Climate Materials

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

Climate Materials Intern

Energy, Environment & Climate Materials

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

Computational Biologist

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Computational Biology Intern

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Computational Energy Scientist

Energy, Environment & Climate Materials

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

Energy & Climate Lead

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.

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

Energy Materials Engineer

Energy, Environment & Climate Materials

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

Energy Research Intern

Energy, Environment & Climate Materials

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

Environmental Nano Engineer

Energy, Environment & Climate Materials

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

Principal Bioengineering Scientist

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Principal Energy Materials Scientist

Energy, Environment & Climate Materials

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

Senior Bio-Nano Engineer

Biology, Biotechnology & Bio-Nano Systems

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

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

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

Senior Energy Engineer

Energy, Environment & Climate Materials

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

2D Materials Engineer

Materials & Advanced Matter

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

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

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

Browse by division

Each division states the scale it works at and the kind of work it does, at the top of its own page.

Ultra-Fundamental & Mathematical Physics

Mathematical and theoretical work on the structure of spacetime, quantum foundations and the frameworks that attempt to describe physics below the Planck length. Entirely theory, mathematics and computation.

Particle, High-Energy & Nuclear Systems

Modelling and data analysis for particle, high-energy and nuclear physics: interaction models, Monte Carlo pipelines, detector data, and radiation effects in materials.

Quantum, Atomic & Precision Systems

Quantum information, algorithms, device modelling, sensing and atomic simulation, in the band where quantum states are measured directly rather than inferred.

Molecular Engineering & Computational Chemistry

Quantum chemistry, molecular dynamics and molecular design: computing what a molecule does, and comparing the prediction with measurement wherever measurement exists.

Nano Engineering & Nanotechnology

Nanomaterials, nanostructures, nanoelectronics, nanophotonics, sensing and metrology, across the band where structures are fabricated, imaged and characterised routinely.

Materials & Advanced Matter

Materials discovery and modelling across alloys, ceramics, polymers, composites, metamaterials, quantum and energy materials, and materials for extreme environments.

Semiconductors, Electronics & Micro/Nano Systems

Device physics, microelectronics and VLSI, MEMS and NEMS, sensors and photonics, in the band where design, simulation and prototype meet.

Computer Science, AI & Scientific Computing

The cross-department division: research software, simulation platforms, HPC, AI for science, digital twins, data pipelines and the reproducibility every other division depends on.

Mathematics & Computational Foundations

The mathematical foundations the whole department stands on: numerical methods, convergence and stability, optimisation, probability, and the modelling support every other division draws on.

Mechanical, Robotics & Multi-Scale Systems

Computational mechanics, robotics, precision engineering and advanced manufacturing, and the multiscale modelling that carries a material property up into a system that has to work.

Civil, Structural & Macro-Scale Systems

Structural engineering, smart infrastructure, advanced construction materials, infrastructure sensing and digital twins, and climate-resilient large-scale systems.

Biology, Biotechnology & Bio-Nano Systems

Nanobiotechnology, biomaterials, biosensors, computational biology and bioinformatics, tissue engineering, lab-on-chip and microfluidics, and the interfaces between biology and engineered surfaces.

Energy, Environment & Climate Materials

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

Aerospace, Space & Extreme Environment Engineering

Aerospace and space systems engineering, extreme-environment materials, orbital and planetary systems modelling, space robotics and the architecture work behind long-horizon space research.

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.