2 of 2 Permanent Statistical Learning Jobs in England

Quantitative Researcher with Machine Learning experience, Systematic Equities Quantitative Researcher with Machine Learning experience, Systematic Equities Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns. Job Description Quantitative Researcher, with machine learning experience, as part of a collaborative team based in … alpha research, with a primary focus on: idea generation, data gathering and research/analysis, model implementation and backtesting for systematic equity strategies Combine rigorous scientific methods and machine learning or statistical learning techniques to explore, analyze, and harness a large variety of datasets in order to build strong predictive models which will be deployed to the … investment process Develop and improve sophisticated python-based software tools and libraries for machine learning researches Write and maintain neat, modular code on a jointly owned codebase of significant size and complexity Collaborate with the SPM in a transparent environment, engaging with the whole investment process Preferred Technical Skills Strong research and programming skills in Python and experience working More ❯

General Theory for Big Bayes" and Grenoble IDEX. Interested applicants should write to us with: a letter of interest, CV, and should require two recommendation letters. Context Bayesian deep learning brings together two of the most important machine learning paradigms: Bayesian inference and deep learning. On the one hand, Bayesian learning provides a theoretically sound framework to … formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution approximations. State of the art The field of machine learning has recently been much impacted by deep learning. Deep neural networks … time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the interaction between these two learning paradigms is relatively under-explored, there is a great potential of cross-fertilisation between the two. Objectives The goal of this project is to contribute new theory and practical More ❯