51 to 75 of 333 Algorithms Jobs in the UK

will be part of a team whos responsibilities include: Building scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Carrying out data analyses to yield actionable business insights. Adhering to and advocate for data science and best

agents, and MCP-based systems. Build, train, fine-tune, and evaluate AIML models for automation use cases. Develop Python-based data pipelines and algorithms using NLTK, NumPy, Scikit-learn, Pandas. Collaborate with cross-functional teams in an Agile setup (sprint planning, refinement, retrospectives). Integrate solutions with test automation frameworks

time permanent basis. This is a hybrid role with occasional travel. Key duties will include but are not limited to: Assist with developing control algorithms to improve the performance of robotic systems. Work closely with the wider team to ensure quality across the full software lifecycle. Produce clear technical documentation

time permanent basis. This is a hybrid role with occasional travel. Key duties will include but are not limited to: Assist with developing control algorithms to improve the performance of robotic systems. Work closely with the wider team to ensure quality across the full software lifecycle. Produce clear technical documentation

firmware from concept through to release Program ARM-based microcontrollers and FPGA systems (VHDL/Verilog) Implement real-time systems and signal processing algorithms Work closely with hardware teams to optimise system integration and performance Support testing, validation, and documentation throughout the development cycle About You Proven experience in embedded

skills to real-world challenges. What youll do Develop signal-analysis and measurement software in modern C++ on Windows/Linux. Implement and optimise algorithms for real-time data and signal processing (FFT, filtering, modulation, etc.). Collaborate with DSP, RF, and hardware teams to integrate your code with advanced

this could be the role for you. Key Responsibilities: Plan, deliver, and assess engaging Computer Science up to KS5. Teach key concepts including programming, algorithms, data structures, cybersecurity, and computational thinking. Foster a creative and inclusive classroom environment where students feel confident exploring technology. Prepare students for examinations and real

this could be the role for you. Key Responsibilities: Plan, deliver, and assess engaging Computer Science up to KS5. Teach key concepts including programming, algorithms, data structures, cybersecurity, and computational thinking. Foster a creative and inclusive classroom environment where students feel confident exploring technology. Prepare students for examinations and real

deploying machine learning models in production. Strong proficiency in Python and key ML frameworks ( PyTorch , TensorFlow , scikit-learn ). Deep understanding of machine learning algorithms and statistical modelling. Ability to work independently while collaborating effectively within technical teams. Excellent analytical , problem-solving , and communication skills. NICE TO HAVE: Hands

scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies. Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses. Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability

platform monitors network protocols in real-time, parses the commands and data structures to extract key metadata which is then analysed by in-house algorithms and allows customers to detect hackers, malware, data leakage and other malicious activity. Your role: As a Security Operations Engineer/DevSecOpsyou will play

industry experience , including 5+ years in system architecture within robotics or complex embedded systems. Strong knowledge of robotic system design - including kinematics, dynamics, control algorithms, perception systems, and simulation tools such as Gazebo or Simulink. Experience with hardware-software co-design, real-time computing, middleware, and system integration (including robotic

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities

Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods and belief networks, reinforcement learning and graph neural networks, computational optimisation at scale, algorithms and data structures. Quantum Information Theory Experience working with stochastic data Who Thrives Here You work fast in loosely defined environments. Competing priorities