Supported by Science Foundation Ireland, the University of Limerick wishes to appoint a Post Doctoral Researcher in Statistics to grow its research programme in developing statistical models and algorithms to analyse high-dimensional, multivariate data measured using sensor technology. Such data are now routinely measured in diverse sectors including medicine, the automotive industry, sports, manufacturing and the Internet-of-Things. The development of interpretable, computationally efficient statistical models suitable for complex data of this type has become an important enabling technology, with multiple applications in both academic and industry-relevant questions.
The central objectives of the project are to develop new, robust statistical models to describe the behaviour and relationships between multivariate, high-throughput sensor data and their temporal derivatives (i.e. velocity and acceleration), develop innovative prediction models for multivariate sensor data, construct novel clustering algorithms to identify and summarise important structures in the data, and demonstrate increased computational efficiency, so that the methodology is applicable to modern, large-scale datasets.
This post is currently funded for 3 years and is part of a co-led project with Prof Norma Bargary at UL and Dr Andrew Simpkin at NUI Galway.
The successful candidate will join Prof Bargary’s research group at the Mathematics Applications Consortium for Science and Industry (MACSI) at UL. MACSI is Ireland’s largest applied and industrial mathematics group and works closely with scientists and industrial companies across a wide variety of sectors. MACSI’s aim is to foster new collaborative research, in particular on problems that arise in industry through the application of cutting-edge mathematical and statistical modelling techniques. The candidate will also work closely with Dr Simpkin and collaborators at NUI Galway, and collaborators at the University of Bristol.
Post Doctoral Researcher in Statistics 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 content. Please give date of Viva.
- Demonstrable programming skills in, e.g., R, Matlab, Hadoop, SQL, Python.
- Evidence of and/or publications in developing models or algorithms for high dimensional and/or high-throughput data.
- Strong communication skills.
- Evidenced ability to collaborate with other researchers, and/or experience of participation in interdisciplinary research projects.
Desirable Criteria
- Knowledge of mixed effect models and/or functional data analysis methods.
- Excellent interpersonal, project management and people management skills.
Please click on the Apply button for full job description and application instructions.
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