51 to 75 of 422 Algorithms Jobs in the East of England

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impact environment. The ideal candidate will have a deep understanding of digital signal processing, machine learning, and generative AI models for audio applications. Key Responsibilities: Develop and optimize advanced algorithms for audio signal processing, including signal injection, enhancement, synthesis, restoration, and error correction. Design and train generative AI models to create, process, and analyze audio content. Implement and refine AI More ❯

impactful models through the lens of conceptual soundness and robustness End-to-end processing and modelling of large data sets Familiarity with deploying and maintaining of statistical models and algorithms in a production setting Excellent critical thinking, writing and verbal communication skills High level of competence in Python, Spark, and Unix/Linux scripts Demonstrable experience using distributed systems (for More ❯

impactful models through the lens of conceptual soundness and robustness End-to-end processing and modelling of large data sets Familiarity with deploying and maintaining of statistical models and algorithms in a production setting Excellent critical thinking, writing and verbal communication skills High level of competence in Python, Spark, and Unix/Linux scripts Demonstrable experience using distributed systems (for More ❯

We are seeking a Research Scientist for our quantum algorithms team in London or Cambridge, UK. Our team leads the development, implementation, simulation, and application of quantum algorithms for computational problems of both scientific and practical relevance. In this role, you will contribute to the design of novel quantum algorithms and to the development of techniques aimed at reducing algorithmic … research includes the development of new techniques and quantum computational models aimed at reducing circuit depth and making quantum circuits shallower, as well as the scalable co-design of algorithms with our hardware, including early fault-tolerant protocols and error correction or detection primitives. Our team members regularly publish scientific papers and present their results at leading conferences. In this … computing stack. You will also engage with our academic and industry partners. Key responsibilities: Conduct research on new computational models and techniques to reduce the circuit depth of quantum algorithms Develop and implement novel quantum algorithms integrated with early fault-tolerant protocols and error correction or detection primitives Contribute to end-to-end resource estimation of quantum algorithms under realistic More ❯