진학프로석·박사 채용 접수 플랫폼

Applications are invited for the following Post in the Technological University Dublin: Competition ID: 036724

Post: Post-Doctoral Researcher in Computer Vision & Machine Learning for Road Pavement Assessment (Fixed Term Specified Purpose Wholetime for up to 5 years with initial funding for 24 months) (Reference: 142/2025)

Location: The successful candidate will initially be based in TU Dublin, Grangegorman but may be reassigned at the discretion of TU Dublin. 

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. €48,412 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: 08th May 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 03rd June 2025. The interview assessment will be 40 minutes in length and will include a presentation of 8 minutes duration. The topic of this presentation will be as follows:

“My experience in applying computer vision and machine learning to real world tasks”

Application Details/Procedures:

For further information and to make an online application for the above post please visit

website visit http://www.tudublin.ie/vacancies 

www.tudublin.ie/vacancies 

Technological University Dublin is an equal opportunities employer

Person Specification

TU Dublin is committed to being fully inclusive, which actively recruits, supports and retains staff from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the community they represent. We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices. During the recruitment and section process, candidates will be expected to demonstrate an appropriate mix of knowledge, experience and skills described below. For shortlisting purposes, candidates will be expected to demonstrate the degree to which they meet both the essential and desirable criteria set out below.

The ideal candidate will demonstrate the appropriate mix of knowledge, experience, skills, talent and abilities required for the role as outlined below and must satisfy all of the essential criteria:

Essential

• A PhD in Computer Science or a related field
• Expertise in Machine Learning & Computer Vision research techniques and methodologies – Strong background in developing and applying ML and CV techniques including image processing, segmentation and explanation particularly for image and video analysis 
• Experience with Deep Learning Frameworks – Proficiency in using TensorFlow, PyTorch, or similar frameworks for model development and deployment 
• Strong Data Analysis & Interpretation Skills – Expertise in statistical analysis, anomaly detection, and pattern recognition to extract meaningful insights from road condition data 
• Experience working with Real-World Datasets – Experience in collecting, processing, and analysing large-scale datasets, including annotated images and sensor data 
• Familiarity with handling and processing geospatial imagery, LiDAR, drone footage, or other
• Evidence of a research profile and publication record within the requisite subject area 
• Experience of developing research funding proposals (Essential)
• Effective written and verbal communication skills (Essential)
• Programming & Software Development Skills – Strong coding ability in Python and experience with relevant libraries (e.g., OpenCV, scikit-learn, NumPy, Pandas) (Desirable)
• Evidence of strong collaboration record, particularly with industry partners (Desirable)

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

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.

Further information for Post-doctoral Researcher 

In the case of a 1st Post-doctoral Fellowship where the applicant may not have graduated yet, the successful applicant must, at the time of appointment, provide a letter from the appropriate graduate studies office confirming that the student has completed the programme including all the examination requirements and is just awaiting the formal graduation ceremony and the likely date on which that will take place.