1 to 25 of 54 Permanent Linear Algebra Jobs in England

supporting 5G NR/5G Advanced/6G development and 3GPP RAN1/RAN2 standardisation activities. Candidates should bring expert-level digital signal processing, linear algebra/statistics and algorithm development experience (synchronisation, channel estimation, equalisation/MIMO detection, decoding), strong C++/OO programming, link/system … documentation for the projects assigned. Following the company's life cycle and QA procedures. Essential Experience and Knowledge: Expert-level digital signal processing skills. Linear algebra, probability theory and statistics. Experience of algorithm development (synchronization and tracking, channel estimation, equalization and MIMO detection, de-mapping and decoding ...

Prototype, architect, and code robust gameplay and animation features, ensuring clean memory management, low CPU overhead, and highly modular logic. Math-Driven Animation: Utilize linear algebra and 3D mathematics to implement advanced procedural, kinematic, or dynamic character behaviors. Estimation & Scoping: Support production planning cycles by providing highly accurate … Engine ecosystem. Advanced C++ & Mathematics: High-level proficiency in modern C++, object-oriented (OO) design principles, and a strong foundational mastery of 3D math, linear algebra, and coordinate spaces. GAS Expertise: Practical, production-tested experience utilizing and extending Unreal Engine’s Gameplay Ability System (GAS). Engine Foundations ...

someone who can independently investigate complex problems, work effectively in an established codebase, and grow into broader technical leadership over time. Experience in linear algebra and/orLagrangiananalysis is highly desirable.Programming ability isrequired, but prior C++ experience is not essential.The ideal candidate will have both postgraduate/research … debuggers, performanceprofilersand memory profilers. Experience with source control systems and continuous integration/continuous developmenti.e.git and Azure DevOps. Background in one or both of: Linear algebra Lagrangiananalysis Problem solving– able to break down difficult technical and mathematical problems and develop practical, effective solutions. Critical thinking– evaluates evidence objectively ...

experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit‐learn. Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus. Collaborative, humble and enthusiastic attitude. Preferred Qualifications, Capabilities and Skills Experience deploying on AWS cloud infrastructure using Lambda, Glue ...

/IP DNS NAT TLS/HTTPS Routing Load balancing Firewalls Congestion control Mathematics for Computing Logic Discrete maths Probability Statistics Graph theory Linear algebra Boolean algebra Combinatorics Proofs Number theory Distributed & Cloud Systems Replication Partitioning CAP theorem Event-driven architecture Idempotency Eventual consistency Queues & streams Serverless ...

/or Google ADK. Strong Python and SQL; able to write clean, production-ready code. Strong AI/ML fundamentals, including statistics, probability, linear algebra, and model evaluation. Experience with scikit-learn and either PyTorch or TensorFlow. Practical DevOps mindset: testing, CI/CD, reproducibility, code quality ...

Python are fundamental, alongside proficiency with ML frameworks like TensorFlow and PyTorch. Machine Learning Engineers need solid mathematics and statistics knowledge, particularly in linear algebra, calculus, and probability theory. Experience with cloud platforms (AWS, GCP, Azure) is essential for deploying models at scale. Skills in data preprocessing, feature ...

relational and non-relational databases Experience with AWS cloud services (S3, Lambda, EC2, RDS, Glue, or similar) Strong applied mathematics – statistics, probability, linear algebra, or signal processing Demonstrated ability to read, understand, and extend complex algorithms and dense business logic written by others Understanding of software engineering principles ...

data pipelines and ETL processes, directly contributing to the team's delivery of secure and stable data architectures Applies advanced data modeling techniques, including linear algebra, statistics, and geometrical algorithms to solve real world business challenges and drive actionable insights Collaborates closely with cross-functional teams to integrate ...

equivalent in Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering etc.)Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra. Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks ...

with natural language processing technology, including LLMs and prompt engineering is a plus Strong quantitative skills with demonstrated understanding of mathematics, probability, statistics and linear algebra Nuanced understanding of economic and financial concepts and demonstrated intuition around applying these concepts in a quantitative environment Ability to work independently ...

software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design) Demonstrated mathematical maturity — comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability Deep proficiency in Python; experience with R and/or C/C++ is a strong plus Extensive experience ...

frameworks for building with large language models alongside libraries such as pandas, NumPy and scikit-learn. Strong mathematical and statistical foundations, including probability, statistics, linear algebra and optimization, and the ability to reason rigorously about uncertainty, error and model behavior. A sound grounding in machine learning, including model ...

takes to move from concept to production A strong mathematical background; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with ...

cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions. Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation. A strong product mindset with the ability to operate autonomously while working in a cross-functional and cross-team environment. Good ...

cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions. Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation. A strong product mindset with the ability to operate autonomously while working in a cross-functional and cross-team environment. Good ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database ...

Electrical Engineering, Statistics, or equivalent fields. Applied AI experience (generative AI, agentic solutions, regression and classification, supervised, and unsupervised learning). Strong mathematical background (linear algebra, calculus, probability and statistics).Experience with scalable ML (MapReduce, streaming).Ability to drive a project and work both independently ...

with experience in either computer vision, foundation models, or 3D medical imaging. Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. ...

with experience in either computer vision, foundation models, or 3D medical imaging. Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...

risk with good understanding of risk modelling. Credit experience is preferred. Very good grasp and understanding of mathematical concepts like probability, statistics, stochastic calculus, linear algebra, Monte Carlo techniques. MSC in a related discipline Good knowledge of Python, SQL, Matlab, VBA. Good understating of financial products (Bonds, Derivatives ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...