HIRING: Post Doctoral Researcher in Data Science/Machine Learning

A doctoral degree (level 10 NFQ), completed or in the final stages of completion, in statistics, mathematics, applied mathematics, data science or related field with significant statistical and/or machine learning content. Please give date of Viva in application.

OVERALL PURPOSE OF THE JOB:

The University of Limerick wishes to appoint a Post Doctoral Researcher to develop our research programme in data analytics, to enable our manufacturing vision and to transform and grow our industry partner’s manufacturing research base. The successful candidate will be based at the Mathematics Applications Consortium for Science and Industry (MACSI), Ireland’s largest applied and industrial mathematics group. MACSI works closely with scientists and industrial companies across a wide variety of sectors with the aim of fostering new collaborative research, in particular on problems that arise in industry through the application of cutting-edge mathematical and statistical modelling techniques.

The position will be co-funded by the Science Foundation Ireland Research Centre in smart manufacturing, Confirm (www.confirm.ie), and a multinational industry partner. Confirm was launched in 2017 and includes 9 academic partner institutions (UL, LIT, UCC, CIT, NUIG, AIT, IT Tralee, NUI Maynooth and Tyndall National Institute) and over 40 industrial partners. Confirm focuses on manufacturing research at a systems level, where we take data from discrete production processes using bespoke sensors, use manufacturing data analytics to extract relevant data to drive predictive models and algorithms of production in order to make smart decisions to be fed back to the machine controllers and robots, all implemented through secure ICT software loops linking the systems. This research programme focuses on developing data analytics aspects to achieve this overall mission.

Confirm has a dual research focus – it carries out an industry-targeted research programme in collaboration with industry partners, in addition to a fundamental research programme that underpins future developments in Manufacturing Systems. This project will be carried out as part of an industry-targeted research programme in close collaboration with our industry partner.

The successful candidate will develop a novel combination of machine learning, statistics and reliability modelling to analyse the company’s large datasets measured in field across numerous sites nationally and internationally. Key outputs include extract key features of interest, discovery of customer workflow patterns, understand product failure mechanisms and forecast product lifetimes.

DESCRIPTION :

Research

• Contribute to the research programme of the Department under general guidance of a member of the academic staff or Principal Investigator/Project Leader.
• Define research objectives and proposals for own (or joint) research in line with research strategy.
• Conduct individual and/or collaborative research projects in a variety of settings (laboratory, creative performance, field, clinical setting).
• Determine appropriate methodologies for research, with advice and support as appropriate.
• Assess research findings for the need/scope for further investigations/commercial exploitation.
• Translate knowledge of advances in the subject area into research activity.

Research Management

• Plan, co-ordinate and implement research project (this may include managing a small research team/co-ordinating other researcher activity).

Income Generation/Funding

• May identify sources of funding and pursue the process of securing funds.
• May work with PI to contribute to proposals for developmental purposes.

Research Outputs-Write Up and Dissemination

• Write up results from own research activity.
• Contribute to the research project’s dissemination, in whatever form (report, papers, chapters, book).
• Present information on research progress and outcomes e.g. to bodies supervising research; conferences, steering groups; other team members, as agreed with the PI/Project Leader.
• Where appropriate, work with PI to register patents to protect intellectual property.

Supervision

• May act as co-supervisor or be a member of a supervision panel.
• May participate in limited teaching hours for own development. The extent of this must not adversely affect the primary research role.

Policy & Standards

• Knowledge and understanding of the policy, practices and procedures, relevant to the role, which may include broader university/sector/external sponsor or funder (e.g. Commercial Awareness, Research Ethics, Knowledge Transfer, Patents, Intellectual Property Rights, Health and Safety, Equal Opportunities & Diversity).
• Legal requirements regarding data protection and confidential data protection requirements.

Essential Criteria

• A doctoral degree (level 10 NFQ), completed or in the final stages of completion, in statistics, mathematics, applied mathematics, data science or related field with significant statistical and/or machine learning content. Please give date of Viva in application.
• Strong programming skills in, e.g. R, Matlab, Python.
• Strong communication skills and well-developed ability to communicate technical concepts to non-experts.
• Strong examples of ability to collaborate, in particular with industry partners, with evidence of participation in interdisciplinary research projects.
• Experience working with large and diverse datasets and/or relevant publications in the modelling and analysis of large datasets.

Desirable Criteria

• Experience of and/or publications in the development of and/or application of statistical or machine learning models and algorithms to large datasets.
• Experience with Hadoop/SQL.
• Experience of collaboration with industry partners and awareness of the importance of intellectual property management and protection.
• Excellent interpersonal and project management and/or people management skills.

• Full title of PhD thesis.
• Full list of publications including weblinks to publications.