Location: Trinity College Dublin
Level: Primary university degree

Expected start date: 1 September 2020

Post summary

A doctoral student in STEM (Science, Technology, Engineering, Mathematics) is required to conduct and assist research at Trinity College Dublin on a new research programme called FRAILMatics: Mathematical research and big data analytics towards the development of the next generation of transdisciplinary diagnostics for the assessment of physiological vulnerability in older adults: challenge-based disruptive technology initiative. This research programme is funded by Science Foundation Ireland (SFI) under the 2018 President of Ireland Future Research Leaders Programme, awarded to Principal Investigator Prof. Roman Romero-Ortuno. The grant runs from 1 December 2019 to 30 November 2024 (60 Months).

The researchers on this grant will be contracted for 4 years (expected start date: 1 September 2020).

Prof. Ortuno is a Clinician Scientist in Geriatric Medicine with skills and international experience in big data analytics and clinical bioinformatics collaborations. Through this SFI award, he will recruit and lead a new transdisciplinary lab of two experienced post-doctoral researchers (one in STEM and one in Health) and two PhD students (one in STEM and one Medical) with the overall objective to advance the science of frailty in older adults. This new lab will be embedded within the state-of-the art research facilities of The Irish Longitudinal Study on Ageing (TILDA) in Trinity College Dublin, and the Mercer’s Institute for Successful Ageing (MISA) in St James’s Hospital, Dublin; in both locations, a new High Performance Computing (HPC) infrastructure will be available to the team which is also funded by the award. FRAILMatics has collaborators at the SFI-funded ADAPT Centre and the Reilly lab at the Trinity Centre for Biomedical Engineering.

The successful candidate will conduct her/his doctoral research on FRAILMatics’ novel research programme on the dynamic modelling of frailty in older adults. She/he will work under the guidance of the postdoctoral STEM and HEALTH researchers and report to the Principal Investigator.

Funding Information

  • This research programme is funded by Science Foundation Ireland (SFI) under the 2018 President of Ireland Future Research Leaders Programme, awarded to Principal Investigator Prof. Roman Romero-Ortuno.

Further Information

  • Informal enquiries about this post should be made to Prof. Ortuno at romeroor@tcd.ie.

Standard Duties and Responsibilities of the Post

  • Register for a PhD degree and conduct doctoral research under the direction of the Principal Investigator (Prof. Roman Romero-Ortuno) on FRAILMatics, which is the research grant from which her/his stipend will be paid. PhD registration fees in Trinity College Dublin will be covered by the programme.
  • Assist with the management of the datasets and prepare data for machine/deep learning analyses ensuring its reliability and usability in a variety of computer programmes.
  • Contribute her/his STEM expertise to perform quantitative data analyses and support the machine/deep learning processes.
  • Cooperate with the TILDA management team and abide by operational policies at all times.
  • Present findings to interdisciplinary audiences at seminars and conferences.
  • Contribute to the organisation and running of the planned FRAILMatics’ small-scale patient engagement and Patient-Public Involvement (PPI) events.
  • Generate internationally peer-reviewed publications in high-impact scientific journals.

Person Specification

Qualifications Essential

  • Primary university degree in a relevant STEM (Science, Technology, Engineering, Mathematics) discipline.

Desirable

  • MSc in a relevant STEM discipline.

Knowledge & Experience (Essential & Desirable) Essential

  • Good communication, writing, verbal, and organisational skills.
  • Ability to work independently and effectively as a member of a team.
  • Ability to communicate clearly with researchers from other research disciplines.
  • Evidence of scholastic achievements.
  • Willingness to learn new methods.

Desirable

  • Experience in quantitative data analyses.
  • Interest in health-related research.

Full application details can be found here