Location: Trinity College Dublin
An experienced post-doctoral researcher in STEM (Science, Technology, Engineering or 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 postdoctoral STEM candidate will lead FRAILMatics’ analytics and machine/deep learning processes. The postdoctoral STEM researcher will work in collaboration with the postdoctoral Heath researcher and report to the Principal Investigator. She/he will also assist the PI with the academic supervision of both doctoral students.
- Informal enquiries about this post should be made to Prof. Ortuno at firstname.lastname@example.org.
Standard Duties and Responsibilities of the Post
The post holder will be expected to:
- Conduct research under the direction of the Principal Investigator (Prof. Roman Romero- Ortuno) on FRAILMatics, which is the research grant from which her/his salary will be paid.
- Lead FRAILMatics’ analytics and machine/deep learning. The postdoctoral STEM fellow will work in collaboration with the postdoctoral Heath researcher and report to the PI. She/he will assist the PI with the academic supervision of both doctoral students.
- Inform, if necessary, the expansion of the High Performance Computing (HPC) system based in TILDA. Procurement of this system is already in progress and an initial solution will be in place by September 2020. Subject to budget availability, there is a possibility for expansion of the HPC system once the successful STEM post-doc candidate is appointed.
- 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.
- Collaborate with FRAILMatics’ official collaborators and other researchers as specified by the Principal Investigator.
- Cooperate with the TILDA management team and abide by operational policies at all times.
- Prepare progress and technical reports on the research conducted under FRAILMatics.
- Present findings to interdisciplinary audiences at seminars and conferences.
- Represent FRAILMatics in discussions at public, technical and scientific fora.
- Contribute to the organisation and running of the planned FRAILMatics’ small-scale patient engagement and Patient-Public Involvement (PPI) events.
- Disseminate results to policy makers, healthcare professionals and other stakeholders through various means including research briefs.
- Seek innovative opportunities for knowledge exchange and dissemination of results.
- Generate internationally peer-reviewed publications in high-impact scientific journals.
- Support the Principal Investigator in intellectual property-related matters arising from the research (e.g. Invention Disclosure Forms, Patents).
- Identify and develop funding applications for any further studies that may be necessary from hypotheses or prototypes developed during the course of the research programme.
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.
- Candidates must hold a PhD degree in a relevant STEM (Science, Technology, Engineering or Mathematics) discipline.
- A machine/deep learning qualification (or attainment of recognised course) is desirable.
Knowledge & Experience (Essential & Desirable) Essential
- Experience in statistics/data analysis/machine learning or deep learning.
- Experience working with large cross-sectional and longitudinal datasets.
- Excellent computing, communication, writing, and organisational skills.
- Proven track record of international peer-reviewed publications.
- Post-PhD professional experience.
- Experience working in an interdisciplinary team.
- Experience using High Performance Computing clusters.
- Experience in a leadership role in a research group or laboratory.
- Demonstrated capability to exercise independence in research as evidenced by, for example, senior authorship/sole authorship of publications, and invited presentations at conferences.
- Past attainment of research funding as PI, co-PI or collaborator.
- Past attainment of intellectual property as inventor or co-inventor.
- Understanding/experience of software package development/integration.
- Demonstrated capability and interest in teaching, especially to disciplines other than her/his own.
Skills & Competencies Essential – methods
- Experience in general statistical applications.
- Experience in supervised and unsupervised learning as well as predictive analytic methods.
Essential – software
- Experience in a programming language such as Python/R/Matlab/C++.
- Experience programming/scripting in Linux operating system (e.g. Linux Shell).
- Experience in the use of a general statistical package (e.g. SPSS, SAS, STATA, etc.).
Desirable – methods
- Knowledge of data visualisation methods.
- Knowledge of information entropy methods, functional data analyses.
- Ability to apply other mathematical or statistical methods in this novel area of research.
- Ability to develop new mathematical or statistical methods for this novel area of research.
Desirable - software
- Experience with Python libraries for machine learning (e.g. Tensorflow, Pytorch, Scikit, Theano, Caffe).
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