7 of 7 Permanent Linear Algebra Jobs

libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases & Querying: Proficiency in SQL for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases ...

Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations (calculus and linear algebra highly advantageous). Experience working across the full data science project lifecycle. A pragmatic, engineering-minded approach to data science, with ...

evaluation and scaling. Ability to design, execute, analyse and clearly communicate ML experiments. Mathematical foundations to support the above, including calculus, probability theory and linear algebra. Evidence of research ability, such as conference or workshop submissions, publications, technical reports, open‐source projects or impactful industrial research. Desirable: Experience with ...

deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent). Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions. Demonstrated ability to formulate ambiguous engineering ...

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 ...

math, quantitative finance, or other quantitative fields with a strong foundation in statistics Demonstrated proficiency in Python Strong command of foundations of applied statistics, linear algebra, and time series models Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources Knowledge of financial markets Highly ...

developing applications and algorithms for Fault Tolerant Quantum Computers, hybrid quantum-classical workflows, classical circuit simulation using High Performance Computers. Application areas include Quantum Linear Equation Solvers, state and matrix loading, block encoding, measurement observables and state reconstruction including machine learning and data science. The team aims to radically … will focus on error-corrected algorithms and develop practical applications that can be run in emulation in advance of using physical devices. For Quantum Linear Equation Solvers, this will build on our existing expertise in Quantum Singular Value Transformation and extend into new areas such as solving time-dependent ...