Data Analyst in Asset Management and Machine Learning (KTP Associate)

Data Analyst in Asset Management and Machine Learning (KTP Associate)

University of the West of Scotland / IMRANDD Limited
Location: Aberdeen
Salary: Up to £40k + £6k personal development budget
Closing Date: 30th May 2019
 

REQ000736
Up to £40k + £6k personal development budget + opportunity to do a higher degree (PhD) at no cost;
36 month fixed term post with potential for permanent employment
Gain management experience and training
Apply your degree and lead your own project in a business
Work with senior company management to realise benefits to the business

IMRANDD is a business focused multidiscipline group of engineers and oil and gas professionals with broad experience in the management of upstream oil & gas assets. They have extensive background in asset integrity management and can provide specialist engineering support and solutions for fixed and floating offshore structures, marine systems and pressure systems.

IMRANDD is looking to become the #1 independent provider of asset integrity assessment and management consulting services within the Oil and Gas Sector. Central to this ambition is the creation of strategic differentiation through the introduction of disruptive technologies around data analytics, deep learning and automation, particularly with regard to risk analysis.

Find out more by visiting:  http://www.imrandd.com/#intro

University of the West of Scotland (UWS) and IMRANDD Limited are offering an exciting opportunity to a post graduate in Computer Science/Software Engineering/Information Technology or with a relevant degree involving a significant amount of software development to support IMRANDD Limited Systems. 

The successful candidate will be a trusted member of the research and development team and will be expected, with support from a highly cooperative community of academic experts.  Responsibilities will include the Strategic assessment of the technical challenges and business opportunities of IMRANDD, the Technical Review and Design Specification to deliver a prototype and the development of the IMRANDD’s asset integrity management framework using deep learning techniques

Infographic on AI and ML companies

About KTP:
This position forms part of the Knowledge Transfer Partnership (KTP) funded by Innovate UK.  It’s essential you understand how KTP works with business and the University, and the vital role you will play if you successfully secure a KTP Associate position. 

Please visit: www.ktpws.org.uk

The successful candidate must possess:
Educated to post graduate level in Computer Science/Software Engineering/Information Technology or a relevant degree that combines aspects of software development

Experience of software development in C/C++, Python or Matlab  is essential and familiarity with the following technologies would be an advantage: Natural Language processing, artificial neural network, deep learning, Artificial Intelligence, Big Data, asset integrity management

Knowledge of programming language C/C++, PythonAPIs (client and server); Cloud infrastructure; GNU/Linux; HTML/CSS; MariaDB/MySQL; Mathematical modelling; Perl; PHP; Scalable services

Essential skills we require as a minimum:
Organisational skills with the ability to plan under own initiative and to work to deadlines
Good communication and interpersonal skills including report writing
Ability to collaborate with colleagues and sharing expertise.
Strong analytical and numerical skills
Ability to understand and process data

If you have questions about this vacancy contact:

T: Prof Naeem Ramzan, 0141 848 3648 or Mr Innes Auchterlonie /Mr Sripad Gopala
E: naeem.ramzan@uws.ac.uk or innes.a@imrandd.comsripad.g@imrandd.com

For more information and to apply please click here

Closing date: 30th May 2019
Interviews: Week commencing 10th June 2019

UWS is committed to equality and diversity and welcomes applications from underrepresented groups.

UWS is a “Disability Confident” employer.

University of the West of Scotland is a registered Scottish charity, no. SC002520

 

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