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Job Opportunity: Research Associate / Senior Research Associate - Machine Learning for Financial Inv:Job description:Job location: Bristol The function This fixed-term research post is part of the Stratlib.AI project funded by Innovate UK. Stratlib.AI aims to offer businesses a flexible and trustworthy platform to generate bespoke investment analytics, optimised using cutting edge artificial intelligence (AI) / machine learning (ML) techniques. The Stratlib.AI consortium includes financial industry partners and academic partners at the University of Bristol and the University of Birmingham. located at the University of Bristol, this research post will focus on developing a suite of configurable machine learning models appropriate for classification and regression tasks in the application areas of asset management and credit management. Essential skills include skills in machine learning applications and theory. Candidates with practice working with timeseries data and/or financial datasets will be considered favourably. What will you be doing? The function holder will be responsible for developing a suite of models offering varying levels of complexity and interpretcapability (e.g., linear regression and Bayesian models, decision trees and random forests, and deep neural network approaches). Working in collaboration with industry and academic partners, the prosperous candidate will co-develop interactive tools for non-expert users to select, configure, train, and test these machine learning models while offering guidance and best practice. Outputs will be incorporated into a commercial platform for financial investment management. You should apply if You have » BSc or MSc degree in computer science, or closely related field. » PhD in Computer Science or related discipline (or near completion), with a focus on applications of machine learning. » skills in AI / machine learning applications in finance. » skills in machine learning for timeseries data. Please read the attached Job Description for further details. Additional information Salar: Grade I £37,099 - £41,732 per annum; Grade J £41,732 - £46,974 per annum For informal queries Contact Us byDr John Cartlidge, email: john.cartlidge@bristol.ac.uk. To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog: https://engineeringincludesme.blogs.bristol.ac.uk/ Interviews are anticipated to be held on 13 May 2024. Our strategy and mission We recently launched ourstrategyto 2030 tying together our mission, vision and values. The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in aninclusive working environment where all colleagues can thrive and reach their full potential.We wantto attract, develop, and retain individualswith different practices, backgrounds and perspectives - particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution. Skills:
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