About the role

You’ll own our first atomistic simulation campaign on an ultrathin, vapour-deposited hybrid material that has never been simulated: predicting conductivity (electron, ion, heat), hydration behaviour and interfacial transport, and testing your predictions against experiments we’ll run constantly alongside. The workflow (DFT benchmarking → amorphous structure generation → fine-tuned machine-learned interatomic potentials with active learning → large-scale transport MD, enhanced sampling and path-integral MD) is scoped, budgeted and precedented in the recent literature; the material is not. You’ll be our first dedicated computational hire, working directly with the experimental team.

What you’ll do

• Benchmark DFT functionals against coupled-cluster references for proton-transfer energetics, and own the resulting error budget
• Build amorphous model structures of a hybrid metal-organic network, validated against our data
• Fine-tune foundation MLIPs (MACE-class) with active learning; run DFT labelling campaigns
• Run nanosecond-scale transport MD, metadynamics and PIMD to extract diffusion coefficients, activation energies, isotope effects and interfacial behaviour
• Turn simulation into decisions: feed results into our materials and process development, and publish the methodology with us
• Define our simulation infrastructure: environments, data management, reproducibility

What we’re looking for

• PhD in computational chemistry, physics or materials science
• Hands-on ab-initio MD experience on HPC
• You’ve trained at least one machine-learned interatomic potential (MACE, NequIP, Allegro, DeepMD, GAP or similar) and can explain how you built the training set and knew it was converged
• Strong scientific Python

Nice to have

• Ion transport background
• Amorphous/disordered structure generation
• Path-integral MD (i-PI), GCMC (RASPA), charge-partitioning workflows, or workflow engines (psiflow, Parsl, Snakemake)
• A benchmark culture: DLPNO-CCSD(T), functional selection, error bars you can defend

About the role

We’re building fuel cell electrodes a different way. Instead of casting nanoparticle inks, we grow the catalyst and the ion-conductive membranes from the vapour phase, atomic layer by atomic layer, improving mass activity, PGM utilisation and durability. The measurements are standard (CO stripping, RDE, GDE half-cell, single-cell MEA testing under DOE-style protocols) for a non-standard electrode: no one has characterised a catalyst layer built this way. Our films are grown from bespoke organic precursors, and you’ll design, make and purify them too. You’ll be our first dedicated electrochemistry hire, working directly with the deposition team.

What you’ll do

• Electrochemical characterisation of our vapour-deposited catalyst layers: CO stripping and H-upd for ECSA and PGM utilisation, RDE/RRDE, GDE half-cells, EIS. Build the protocols, reference standards and error bars
• Take films to devices: fabricate MEAs from our electrodes, run single-cell PEM and AEM fuel cell tests, decompose polarisation curves into kinetic, ohmic and transport losses, and run accelerated stress tests
• Design, synthesise and purify the organic precursors and molecular building blocks we deposit: bifunctional linkers, ion-conducting units. Qualify them for vapour delivery (NMR, MS, TGA, vapour pressure, thermal stability)
• Work with the deposition team on surface chemistry: precursor reactivity, nucleation on carbon and PGM surfaces, growth inside porous supports
• Help build the electrochemistry lab: test stations, half-cell hardware, gas handling, data pipeline

What we’re looking for

• PhD in chemistry, chemical engineering or materials science with a core in fuel cell electrocatalysis (ORR/HOR on PGM and non-PGM catalysts)
• Hands-on RDE and single-cell MEA testing
• Practical synthetic organic chemistry: Schlenk/glovebox technique, purification, NMR

Nice to have

• ALD, MLD or CVD experience: precursor chemistry, surface reactions, thin-film characterisation
• Ionomer and polymer-electrolyte chemistry (PFSA, hydrocarbon or anion-exchange) and the ionomer–catalyst interface
• PEM/AEM electrolyser or AEMFC experience

About the role

You’ll run the deposition tools and keep the science moving day to day: ALD/MLD runs, sample prep, standard characterisation, and clean, well-recorded data. You’ll work alongside our research chemists and report to the Head of Lab Operations. Our Berkeley lab is opening now, with the first reactors installed in about a month.

What you’ll do

• Operate ALD/MLD reactors for routine deposition runs: execute recipes, run witness wafers, keep the run log
• Prepare substrates, precursors and samples; handle pyrophoric precursors (TMA, DEZ) and ozone to SOP once trained
• Run standard characterisation: ellipsometry, XRD, SEM/EDS, BET, electrochemical testing
• Support synthesis work for the research chemists: simple organic and inorganic prep, solution handling, glovebox work
• Reduce and plot data (Python or Excel); keep sample tracking and records accurate
• Maintain calibration, consumables and lab inventory; follow and help refine SOPs and safety protocols
• Flag anomalies early

What we’re looking for

• Hands-on time in a chemistry, materials or semiconductor lab: glovebox, vacuum tools or cleanroom
• A degree in chemistry, materials science, chemical engineering, physics or similar; undergraduate through postdoc all welcome
• Meticulous, methodical, and genuinely cares about the quality of their work
• Comfortable with vacuum systems, gas handling and standard lab safety practices
• Clear written communication
• Able to work on-site in Berkeley with existing US work authorisation

Nice to have

• Direct experience with ALD, CVD, sputtering or other vapour-phase deposition
• Electrochemical testing or fuel cell / electrolyser MEA fabrication
• Python for data handling and plotting
• Experience commissioning new equipment from scratch

Not required

• A PhD
• Prior ALD experience
• Fuel cell or catalysis background