Scholarships in Responsible AI Software Engineering (RAISE)

Updated: about 2 months ago
Location: Melbourne, VICTORIA
Deadline: 15 Oct 2023 ; 15 Oct 2023

Scholarships in Responsible AI Software Engineering (RAISE)

Job No.: 656326

Location: Clayton campus

Employment Type: Full-time

Duration: The scholarship may be held for up to 3.5 years (full time) for Research Doctorate (PhD) studies

Remuneration: The successful applicant will receive a Research Living Allowance, at current value of $40,500 AUD per annum for PhD (tax free stipend)

The Opportunity

This opportunity is limited to Australian citizens, Australian Permanent Residents, NZ Citizens and a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time.

We are seeking a highly motivated and talented PhD student to join our cutting-edge research team in the field of Responsible Artificial Intelligence (AI) in MLOps. The selected candidate will play a pivotal role in advancing the understanding and application of AI technologies within the framework of ethical considerations, social impact, and operational efficiency. This scholarship offers a unique opportunity to contribute to both the theoretical aspects of AI ethics and the practical implementation of responsible AI solutions in Machine Learning Operations (MLOps) pipelines.

Join us in shaping the responsible AI landscape and driving innovations that prioritize ethical considerations while delivering impactful AI solutions in MLOps environments. Your research can make a significant contribution to both academia and industry, driving the responsible adoption of AI technologies.

Benefits

  • Opportunity to work at the forefront of responsible AI research, addressing critical challenges in the field
  • Access to state-of-the-art computational resources and research facilities
  • Collaboration with leading experts in AI ethics, machine learning, and MLOps
  • Financial support for conference attendance, research-related expenses, and professional development
  • Networking opportunities with academia, industry partners, and policy organizations
  • Potential for co-authoring research papers, contributing to open-source projects, and patent filings

Key Responsibilities

  • Conduct original research to develop novel methodologies, algorithms, and frameworks for integrating responsible AI practices into MLOps workflows
  • Investigate ethical considerations related to AI model development, deployment, and monitoring, with a focus on fairness, transparency, accountability, and bias mitigation
  • Collaborate with cross-functional teams to design, develop, and implement responsible AI solutions that align with industry standards and regulatory requirements
  • Design and conduct experiments to evaluate the performance and ethical implications of AI models and systems in real-world scenarios
  • Publish research findings in top-tier conferences and journals in the fields of AI, machine learning, and ethics
  • Stay current with the latest advancements in AI ethics, MLOps, and related domains, and contribute to the team's knowledge base
  • Engage in academic and industry collaborations to foster a vibrant research community and promote the adoption of responsible AI practices

Candidate Requirements

  • Enrolment in a PhD program in Computer Science, Machine Learning, Data Science, Ethics, or a related field
  • Strong background in machine learning, deep learning, and AI ethics, as evidenced by coursework and/or previous research
  • Proficiency in programming languages such as Python, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
  • Familiarity with MLOps principles, including model deployment, monitoring, and version control, is desirable
  • Excellent problem-solving skills and the ability to think critically about ethical challenges in AI technology
  • Effective written and verbal communication skills, demonstrated through publications, presentations, or other forms of scientific communication
  • Ability to work independently and collaboratively in a research team environment
  • A passion for exploring the intersection of technology, ethics, and societal impact

To be eligible for a scholarship, applicants must be domestic students as per the Higher Education Support Act at the time of award.

Domestic students include:

a. Australian citizens,

b. Australian permanent residents,

c. a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time; or

d. a New Zealand citizen.

Master of Philosophy (MPhil) and Doctor of Philosophy (PhD) scholarship holders must enrol in a full-time degree.

Applicants will be considered provided that they fulfil the criteria for admission at Monash University and demonstrate excellent research capability. Details of the relevant requirements are available at www.monash.edu/graduate-research/future-students/apply.

Scholarship holders must undertake industry placements with industry partner(s) of the program within which the student enrols.

Students who receive a scholarship are expected to undertake their training in Australia and endeavour to remain in Australia for two years following completion of their degree.

Applicants must show excellent communication and interpersonal skills, and the ability to conduct self-motivated research within a high-performing and target-driven group of researchers. Shortlisted candidates will be interviewed, over Zoom if necessary. The interviews will be conducted in English.

The successful applicant will be expected to enrol by January 2024.

Submit an Expression of Interest (EOI) which shall comprise:

  • A curriculum vitae, including a list of published works
  • A full statement of academic record, supported by scanned copies of relevant certified documentation
  • Contact details of two academic referees
  • Evidence of English-language proficiency (if you have)
  • Any achievement records

To apply, please click here .

Enquiries

Dr Kla Tantithamthavorn, chakkrit@monash.edu

Closing Date

Sunday 15 October 2023, 11:55pm AEDT

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