Quantum Physicist (PhD/MSc with Experience Only

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This role is for a Quantum Physicist (PhD/MSc) with expertise in quantum sensing, geophysical modelling, and laboratory experiments. The contract is for 3 months, remote in the UK, with a competitive pay rate. Essential skills include Python and signal processing.

Location: UK (Remote)

Contract: 3 months (with potential for 18‑month extension)

Start: January 2026

Salary: Competitive / negotiable

Organisation: Entergaia Technologies – Quantum Sensing & Subsurface Intelligence

Physics Modelling & Simulation

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• Develop forward models for quantum gravimeter response to voids, sinkholes and water ingress, and quantum magnetometer response to ferrous and geological structures.
  
• Implement analytical or numerical models for mass‑density contrasts, gravitational fields and gradients, magnetic susceptibility contrasts.
  
• Create realistic, physics‑accurate synthetic datasets for AI training.
  
• Model the sensor’s transfer function, including vibration coupling, laser phase noise, interferometer stability and gravity‑gradient / magnetic‑gradient effects.
  
• Work closely with the AI Specialist to verify the realism of simulated signatures.
  

Laboratory Calibration & Controlled Experiments

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• Prepare and configure the quantum sensor testbed (atom interferometer alignment, optical system stability, magnetometer sensitivity optimisation, vibration isolation and environmental control).
  
• Run controlled experiments with known reference anomalies (known masses, void analogues, water‑equivalent targets, magnetic inclusions).
  
• Quantify sensor sensitivities: sub‑µGal (gravity) and pT‑fT (magnetics).
  
• Characterise repeatability, drift, temperature dependence and noise bandwidths.
  
• Collaborate with NPL to obtain traceable metrology validation.
  

Sensor Interpretation & Noise Analysis

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• Decompose recorded signals into true anomaly signatures, platform‑induced noise, environmental artefacts and quantum projection noise.
  
• Model motion‑induced biases using IMU data.
  
• Support the AI team by delivering corrected time series, noise models and uncertainty estimates.
  
• Recommend optimised data‑acquisition protocols for future field deployments.
  

Integration with AI

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• Translate physics constraints into data features.
  
• Define physically plausible anomaly signatures.
  
• Validate AI‑detected anomalies for physical consistency.
  
• Guide feature engineering (gradients, curvature, bandwidth of anomalies).
  
• Assist in fusing gravity & magnetic data into a joint physical interpretation.
  

Technical Leadership in Hazard Interpretation

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• Determine detection thresholds for each hazard type (minimum void size, maximum detectable depth, water ingress sensitivity).
  
• Build capability envelopes (performance charts).
  
• Provide scientific assessment of feasibility.
  

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• Quantum Sensing & Atomic Physics – experience with cold‑atom interferometry, quantum gravimetry, or atomic magnetometry; understanding of Rabi/Raman transitions, laser phase noise, atom optics, magnetic resonance in atomic vapour cells.
  
• Geophysical Modelling – understanding of gravity and magnetic fields in Earth sciences; forward modelling and inversion experience.
  
• Laboratory Experimental Skills – hands‑on experience building or operating optical setups, vacuum systems, laser systems, magnetically shielded environments; design and run controlled physics experiments.
  
• Signal Processing – analysing noisy scientific data; FFTs, PSD analysis and filtering.
  
• Software Skills – Python, MATLAB, or similar scientific computing tools; modelling libraries such as SciPy, NumPy, Fatiando a Terra, QuTiP, COMSOL (desirable).
  
• Communication – explain complex physics to engineers and non‑physicists; strong technical writing for reports and publications.
  

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• Experience with quantum gravimeters from Exail, Muquans, Atomionics, Aquark, or research prototypes.
  
• Understanding of geotechnical engineering or subsurface hazards.
  
• Familiarity with drones, mobile mapping, or rail/road instrumentation.
  
• Knowledge of Bayesian filtering, Kalman filters, or motion‑compensation methods.
  
• Prior work in NPL, university quantum labs, or national labs.
  

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• PhD or MSc in Atomic Physics, Quantum Optics, Quantum Sensing, Experimental Physics or closely related field, OR highly relevant industrial/research experience with proof of technical capability.
  
• Post‑doctoral or industry experience in quantum sensing or precision metrology (preferred).