Senior RF Data Scientist / Research Engineer

• Analysing raw IQ data from SDR platforms (e.g., bladeRF, USRP) to identify, classify, and extract RF signal features
• Building diagnostic tools for RF signal characterisation (e.g., time-frequency plots, cyclic spectra, EVM, autocorrelation, constellation tracking)
• Designing RF data-processing pipelines that account for real-world hardware constraints (bandwidth, gain stages, ADC limits, timing jitter)
• Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy
• Developing machine learning and statistical models for RF classification, anomaly detection, and emitter identification
• Prototyping real-time and batch-processing systems in Python (NumPy, SciPy, PyTorch) and integrating with ZMQ, GNU Radio, or C++ backends
• Leading RF data collection, field experiments, and over-the-air testing with drones, wireless devices, and custom transmitters

Based near Cambridge, we are seeking exceptional Senior Radio Frequency (RF) Data Scientist / Research Engineers to work at the intersection of RF hardware, digital signal processing, and machine learning. You will analyse complex RF data from software-defined radios (SDRs), develop advanced signal-processing pipelines, and contribute to cutting-edge UAV/drone detection technologies. This is a hands-on R&D role suited to someone who thrives in fast-paced prototyping environments. It is a full-time role within the Research & Prototyping team., * Strong Python proficiency for data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch)

• Solid understanding of digital signal processing (FFT, filtering, modulation, correlation, noise modelling, resampling)
• Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR
• Practical understanding of RF hardware chains (antenna -> filters -> mixers -> ADC) and their impact on baseband data
• Experience analysing wireless protocols (Wi-Fi, LTE, LoRa, etc.) and physical-layer structures
• Comfortable debugging SDR setups and carrying out field-based RF data collection
• Strong communication skills and ability to work in an iterative R&D environment
• Hands-on experience with SDRs (bladeRF, HackRF, USRP, PlutoSDR) and RF lab equipment (spectrum analysers, VNAs, signal generators)
• Experience with passive radar, beamforming, TDoA, Doppler, or direction finding
• Familiarity with embedded or real-time systems (e.g., FPGA pipelines, GPU acceleration)
• Programming experience in MATLAB, C++, Rust, or similar
• Knowledge of RF circuit fundamentals (impedance matching, filter design, gain budgeting)
• Experience designing or testing antenna arrays for sensing/detection
• Publications, patents, or open-source RF/ML contributions, * Five days a week on-site (ie: this is not a hybrid role)
• Full UK driving licence required. If this isn’t held, candidates will need to commit to obtaining within 6 months of their start date
• Applicants must be fully eligible to work in the UK without restriction, time limit, or the need for current or future sponsorship

Quell is a high-growth British defence and security AI technology start-up developing solutions to counter drone, vehicle, and human threats across the military, civilian and critical national infrastructure sectors.