3 of 3 Statistical Modelling Jobs in Cambridgeshire

Data Science Trainee

Hiring Organisation
ITOL Recruit
Location
Peterborough, Cambridgeshire, England, United Kingdom
Employment Type
Full-Time
Salary
£30,000 - £50,000 per annum
Data Scientist. This builds on the knowledge of the Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply … mathematical and statistical methods appropriately. Step 5 is not a requirement for our job guarantee as this stage is designed to advance your data career to the next level. Our money back guarantee If after 1 year of passing your formal qualifications, we have been unable to help ...

Senior RF Data Scientist / Research Engineer

Hiring Organisation
Adria Solutions
Location
Cambridge, Cambridgeshire, England, United Kingdom
Employment Type
Full-Time
Salary
£80,000 - £110,000 per annum, Negotiable
cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (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 ...

Senior RF Data Scientist / Research Engineer

Hiring Organisation
Adria Solutions
Location
Cambridge, Cambridgeshire, East Anglia, United Kingdom
Employment Type
Permanent
cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (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 ...