Post-Doctoral Researcher in Quantum Machine Learning for Dependable Network

Post-Doctoral Researcher in Quantum Machine Learning for Dependable Network

Join to apply for the Post-Doctoral Researcher in Quantum Machine Learning for Dependable Network role at Technological University Dublin

Post-Doctoral Researcher in Quantum Machine Learning for Dependable Network

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Applications are invited for the following Post in the Technological University Dublin: Competition ID: 036623

Post: Post-Doctoral Researcher in Quantum Machine Learning for Dependable Networks and Data Stewardship (Fixed term specified purpose for up to 5 years with initial funding for 12 months) (Reference: 311/2024)

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. €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: 01st 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 4th Of June 2025. The Interview Assessment Will Be 50minutes In Length And Will Include a Presentation Of10 Minutes Duration. The Topic Of This Presentation Will Be As Follows

Harnessing Quantum Machine Learning/Machine Learning for Reliable Communication/Computer Networks and Case Studies in Data Stewardship.

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

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.

Theidealcandidatewilldemonstratetheappropriatemixofknowledge,experience,skills,talent and abilities required for the role as outlined below and must satisfy all of the essential criteria:

Essential

• A PhD in Electronic Engineering, Electrical Engineering, Computer Science or a related field.
• Experience conducting Machine Learning or Quantum Machine Learning and Computer Networking experiments on real platforms, simulators or datasets.
• Evidence of a research profile and publication record in Machine Learning and/or Quantum Machine Learning and/or Computer Networking.
• Experience with data collection, analysis, stewardship from testbeds and/or simulators and interpreting experimental results.
• Effective written and verbal communication skills.
  
  

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

• Familiarity with Quantum Machine Learning simulation environments (e.g., Qiskit).
• Proficiency in relevant programming languages (e.g., Python).
• Experience in implementing Open Science best practices.
• In depth knowledge of modern networking technologies, for example, an understanding of video delivery networks and technologies like Software-Defined Networking.
• Practical experience in developing Machine Learning and/or Quantum Machine Learning solutions.
• Knowledge of quantum computing and communication testbeds.
• Evidence of the ability to form collaborations, particularly with industry partners and the hosts of national testbeds/supercomputing resources.
• Experience in seeking external funding opportunities and preparing research bids.
• Experience working on collaborative projects
  
  

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.

Skills

Researcher machine learining Computer NetworkingSeniority level

• Seniority levelInternship

Employment type

• Employment typePart-time

Job function

• Job functionResearch, Analyst, and Information Technology
• IndustriesEducation

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