51 to 68 of 68 Linear Algebra Jobs in England

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods

Must have) Multi-Dimensional Tensor Networks (Must have) Theoretical physics and statistical physics Dynamic systems (energy landscapes, emergent behaviours) Modelling and simulation Mathematics: Advanced linear algebra, optimisation, numerical methods Information theory Probability, statistics Graph theory Highly Valued: Machine Learning Experience: Specifically in parameter-free learning approaches, Bayesian methods