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Research Associate in Machine Learning-Based Supply Chain Analytics

Applications for this vacancy closed on 30 September 2019 at 12:00PM
<div xmlns="http://www.w3.org/1999/xhtml"> <p></p><p>An exciting opportunity has arisen to join the department as a Research Associate/Assistant. You will be part of a research team that applies machine learning techniques to identify behavioural patterns in supply chain data; build, validate and calibrate models of supply chains; use these models to predict future behaviour; assess effectiveness of these models and solutions in a real environment.</p><br> <p>The postholder will carry out research on the &#8220;A demonstrator and reference framework IoT-based Supply Chain Digital Twin&#8221; project, in collaboration with a research group at the University of Cambridge and a major industrial company, as part of the Pitch-In project (http://pitch-in.ac.uk).</p><br> <p>The successful applicant will possess: a doctoral degree (or be close to completion), in computer science, engineering or related discipline; expertise of machine learning and/or AI; proven ability to write software programs and develop prototype systems for demonstration and experimental learning; knowledge of optimisation techniques; ability to manage own academic research and associated activities.</p><br> <p>This position is offered on fixed-term contract for up to 18 months.</p><br> <p>Whilst the role is a Grade 7 position, we would be willing to consider candidates with potential but less experience who are seeking a development opportunity, for which an initial appointment would be at Grade 6 (&#163;29,176 - &#163;34,804 p.a.) with the responsibilities adjusted accordingly (for Grade 7, you would be expected to hold a doctoral degree in computer science or be close to completion). This would be discussed with applicants at interview/appointment where appropriate.</p><br> <p>The closing date for applications is 12.00 noon on Monday 30 September 2019.</p><br> <p>Our staff and students come from all over the world and we proudly promote a friendly and inclusive culture. Diversity is positively encouraged, through diversity groups and champions, for example www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html, as well as a number of family-friendly policies, such as the right to apply for flexible working and support for staff returning from periods of extended absence, for example maternity leave.</p> </div>
dc:spatial
Department of Computer Science, Parks Road, Oxford.
Subject
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oo:formalOrganization
oo:organizationPart
vacancy:applicationClosingDate
2019-09-30 12:00:00+01:00
vacancy:applicationOpeningDate
2019-09-02 09:00:00+01:00
vacancy:furtherParticulars
vacancy:internalApplicationsOnly
False
vacancy:salary
type
comment
An exciting opportunity has arisen to join the department as a Research
Associate/Assistant. You will be part of a research team that applies machine
learning techniques to identify behavioural patterns in supply chain data;
build, validate and calibrate models of supply chains; use these models to
predict future behaviour; assess effectiveness of these models and solutions
in a real environment.



The postholder will carry out research on the “A demonstrator and reference
framework IoT-based Supply Chain Digital Twin” project, in collaboration with
a research group at the University of Cambridge and a major industrial
company, as part of the Pitch-In ...

An exciting opportunity has arisen to join the department as a Research Associate/Assistant. You will be part of a research team that applies machine learning techniques to identify behavioural patterns in supply chain data; build, validate and calibrate models of supply chains; use these models to predict future behaviour; assess effectiveness of these models and solutions in a real environment.


The postholder will carry out research on the “A demonstrator and reference framework IoT-based Supply Chain Digital Twin” project, in collaboration with a research group at the University of Cambridge and a major industrial company, as part of the Pitch-In ...

label
Research Associate in Machine Learning-Based Supply Chain Analytics
notation
142797
based near
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