Applications are invited for the following Post in the Technological University Dublin: Post: Post-Doctoral Researcher (2 Positions) Research & Innovation (2 Fixed term specified purpose contracts for up to 5 years with an initial funding of 18 months and 12 months respectively) (Reference: 519/2024) Location:The post will be based at one of the TU Dublin Campuses i.e.
Grangegorman (Parkhouse), Blanchardstown or Tallaght.
Hours of Work:A 37 hour working week is in operation.
Salary: The successful candidate will be appointed at point (01) of the Post-Doctoral Researcher Salary Scale i.e.
€47,412 gross per annum.
Remuneration may be adjusted from time to time in line with Government pay policy.
Incremental credit may apply in line with University policy.
Closing Date: 20th January 2025 at 5.00 p.m. (Irish time).
Late applications will not be accepted.
It is anticipated that interviews for this post will take place in week beginning 24th February 2025.The interview assessment will be 50 minutes in length and will include a presentation of10 minutes duration.
The topic of this presentation will be as follows: Leveraging Past Experience: My Approach to Predictive Modelling in the area of AI for Health In this presentation, we would like you to overview how your career achievements so far equip you to work on this research project and to present a research plan that you would employ in the project, based on your background and expertise and knowledge of relevant literature.
Application Details/Procedures: For further information and to make an online application for the above post please visit website visit Technological University Dublin is an equal opportunities employer Person Specification Theidealcandidatewilldemonstratetheappropriatemixofknowledge,experience,skills,talent and abilities required for the role as outlined below and must satisfy all of the essential criteria: Essential Knowledge PhD in a relevant discipline with Research experience or equivalent research experience (at least three years) in the public or private sector(Essential) An undergraduate B.Sc.
(Hons) (NFQ level 8) in Computer Science or a related discipline or equivalent award by an approved degree-awarding authority(Essential) Evidence of research publication record and national/international recognition of achievement within the area of AI for Health(Essential) Ability to work with a range of ML libraries and resources (e.g., scikit, Tensorflow/Pytorch) and/or ML Ops(Essential) Experience Previous experience of working with large clinical datasets (e.g., data wrangling, data mining) following GDPR policies(Essential) Extensive knowledge of statistical and explainable supervised machine learning model development and hands-on experience in developing models (e.g., neural networks, logistic regression, etc.)
and experience in applying explainability methods to interpret models (e.g.
SHAP)(Essential) Experience in writing up research results and preparing manuscripts for publication(Essential) Experience applying machine learning methodology to model stroke outcomes, such as mRS(Essentialfor 12-month role) Extensive knowledge and hands-on experience applying statistical methods for risk modeling in health (e.g., survival analysis and regression methods)(Essentialfor 18-month role) Extensive knowledge and hands-on experience utilizing techniques and methodologies of unsupervised machine learning for model development (e.g., clustering methods, GANs, PCA, etc.
)(Essentialfor 18-month role) Skills, talents & abilities Skilled programmer in one or more of: Python, Julia, R(Essential) Effective written and verbal communication skills with ability to present complex information effectively to a range of audiences(Essential) The successful candidate will be highly skilled and motivated with the ability to work independently and as part of ateam(Essential) Candidates will be shortlisted based on their demonstration of meeting every essential criterion so are asked to clearly outline how their experience and qualifications meet the criteria.
Desirable Experience in preparing deliverables for European (H2020, Horizon Europe projects) (Desirable) Knowledge of time-series analysis (Desirable for 18-month role) Knowledge of federated learning techniques (Desirable for 18-month role) Knowledge of development and implementation of digital twin technology (Desirable for 18-month role) Candidates may be shortlisted on the basis of none, one or more of these desirable criteria and are asked to clearly outline how their experience and qualifications meet the criteria.
Skills: postdoctoral resercher Computer Science data wrangling