51 to 61 of 61 SciPy Jobs in England

Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods

Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods

Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods

Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods

e.g UVM/OSVVM Embedded software development in C, C++ or similar Digital Signal Processing System modelling e.g. Matlab/Python/Numpy/Scipy Agile/Scrum Configuration control, Continuous Integration and Continuous Development etc Domain expertise in a relevant technology area Technical/Team leadership If this

electronics, physics or computer science and have significant skills and experience in the following areas: - Expert Python proficiency for data analysis and prototyping (NumPy, SciPy, PyTorch). - Demonstrable applied experience of digital signal processing (FFT, modulation, noise modelling, resampling). - Experience with SDR frameworks (GNU Radio, SDRangel, SoapySDR). - Understanding

Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep … some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science

Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep … some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science

Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company … some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science

accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless … devices, and custom transmitters Requirements Strong 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

accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless … devices, and custom transmitters Requirements Strong 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