Careers · Research opportunities
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.
1199 opportunities
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Unmanned aerial vehicle systems — airframe, flight dynamics, and mission-system design for drones.
UAV systems fundamentals · Flight dynamics basics · Simulation tools · Documentation + 1 more
Satellite platform and payload technology — distinct from our satellite-data-analytics work, this is about the hardware and mission side.
Satellite technology fundamentals · CubeSat design awareness · Research literature review · Documentation + 1 more
A new research track into space-systems engineering — the end-to-end architecture of spacecraft and satellite platforms.
Space-systems fundamentals · Systems engineering basics · Research literature review · Documentation + 1 more
Applying data-science methods specifically to environmental datasets — climate, emissions, ecological data — as a distinct technical specialisation.
Python/R · Statistics · Environmental data literacy · Machine learning fundamentals + 1 more
Broader green-technology research beyond renewable energy specifically — clean-tech innovations across sectors, as a research-domain scan.
Green technology research · Literature review · Documentation · Analytical thinking + 1 more
Researching circular-economy principles (reduce, reuse, redesign-out-waste) applied to our own operations and as a broader research interest.
Circular economy frameworks · Research literature review · Documentation · Analytical thinking + 1 more
The data-analytics slice of our sustainability practice — turning environmental and operational data into trackable sustainability metrics.
Data analysis (Excel/Python) · Sustainability metrics frameworks · Dashboarding · Documentation + 1 more
A broader ESG internship alongside our existing ESG Analytics role — covering the full Environmental, Social, and Governance practice, not just the analytics slice.
ESG frameworks · Policy research · Documentation · Stakeholder communication + 1 more
Technology built for civic participation and public services — a research domain connecting our smart-cities and public-sector work.
Civic technology research · Documentation · Literature review · Cross-team coordination + 1 more
The planning discipline behind infrastructure decisions — where to invest, what to prioritise — applied to our institutional-network research.
Infrastructure planning fundamentals · Prioritisation frameworks · Research skills · Documentation + 1 more
Sustainability applied to physical and institutional infrastructure — connecting our smart-cities research with our own sustainability practice.
Sustainable infrastructure research · Data analysis basics · Documentation · Literature review + 1 more
The IoT layer of smart-city systems — sensor networks feeding urban-service data — studied as a research domain for the HEI team.
IoT fundamentals · Urban-systems research · Documentation · Literature review + 1 more
Data-driven transportation systems — traffic patterns, transit optimisation — researched as it relates to education-access questions the HEI team studies.
Transportation-systems research · Data analysis basics · Documentation · Literature review + 1 more
The intersection of quantum computing and cryptography — including post-quantum cryptography implications for systems like ours.
Cryptography fundamentals · Quantum computing basics · Research literature review · Technical writing + 1 more
Quantum communication protocols — quantum key distribution and related concepts — studied as theory and simulation, not physical implementation.
Quantum communication theory · Python · Linear algebra · Research literature review + 1 more
Simulating quantum systems classically — a distinct, foundational technique used before real quantum hardware is involved at all.
Python · Quantum simulation libraries (Qiskit Aer or equivalent) · Linear algebra · Benchmarking + 1 more
Analog circuit design — amplifiers, filters, power circuits — the continuous-signal counterpart to digital electronics work.
Analog circuit design · SPICE simulation · Amplifier/filter fundamentals · Lab/testing skills + 1 more
Foundational digital-electronics work — logic design, digital circuit fundamentals — for students building the base skill underneath VLSI/FPGA work.
Digital logic design · Circuit simulation tools · Boolean algebra · Lab/testing skills + 1 more
Verification — proving a chip design actually does what it should before fabrication — a distinct discipline from the design work itself.
Verification fundamentals · Testbench writing · SystemVerilog/UVM basics · Coverage analysis + 1 more
Application-Specific Integrated Circuit design — a step beyond FPGA prototyping, for students interested in chip design specifically targeting fabrication.
Verilog/VHDL · ASIC design flow awareness · Synthesis basics · Timing constraints + 1 more
A developer-focused ROS role alongside our existing ROS Development internship — emphasising application-layer development on top of ROS infrastructure.
ROS/ROS2 · Python/C++ · Application architecture · Testing & debugging + 1 more
Automation from the mechatronics angle — integrating mechanical, electronic, and control systems into one automated whole, complementing our Mechatronics AI internship.
Mechatronics fundamentals · Control systems basics · Systems integration · Documentation + 1 more
Automation systems applied to industrial/manufacturing processes — PLCs, automated workflows — a distinct application domain from research robotics.
Industrial automation fundamentals · PLC/SCADA awareness · Documentation · Research skills + 1 more
The embedded-systems layer of robotics — microcontrollers, real-time constraints, low-level hardware interfacing for robotic platforms.
Embedded C/C++ · Microcontrollers · Real-time systems basics · Motor/sensor interfacing + 1 more
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.