Postdoctoral Research Fellow Position in Knowledge Graph Engineering at the Australian National University

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Application deadline: Jan 6, 2019
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Job: Research Fellow
Work type: Fixed Term
Location: Canberra / ACT / Australia
Classification: Academic Level B
Salary package: $114,670 - $130,297
Term: Full time, Fixed term (3 years)
Apply at: http://jobs.anu.edu.au/cw/en/job/527294/research-fellow



Position overview
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The ANU College of Engineering and Computer Science (CECS) is dedicated to contributing to The Australian National University’s reputation for excellence in research and research-led education, bringing together expertise across a range of areas to reimagine the role of engineering and computing for future generations. CECS is a diverse and vibrant community dedicated to discovery and to making knowledge matter. Our academics and students are engaged in ground-breaking, cutting-edge research, in exciting areas such as renewable energy, robotics, telecommunications, biomaterials, human-machine interaction, and artificial intelligence.

The position is located within the Research School of Computer Science (RSCS) in CECS, a close-knit research and teaching community, made up of high performing academic and professional staff, students and visitors sharing a deep commitment to transforming the future of engineering for the next generation. The appointee is accountable to the Project leader, Dr Armin Haller, and the Director of the Research School. The appointee will liaise with relevant professional and academic staff members within the Research School of Computer Science and the ANU as well as establishing relationships with the wider research community to enhance cross-disciplinary collaborations.

As an academic member of the Research School of Computer Science the appointee will be required to contribute to the overall intellectual life of the School, College and University. This includes contribution to research, education and outreach agendas of the School both nationally and internationally in a manner that is appropriate to the level of appointment. The appointee is expected to undertake independent research activities that are aligned with the School’s strategic priorities that emphasise relevant and translational research.

This position is a fixed term for a period of three (3) years appointment to contribute to the objectives of an externally funded project with the Department of Finance on “An ontology framework for government information”. Applications are particularly invited from researchers whose expertise are in the areas of Ontology Engineering, Machine Learning, Knowledge Graphs, the semantic Web and Linked Data and whose breadth of vision reaches across traditional discipline silos. We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from individuals who may have had non-traditional career paths, who may have taken a career break or who have achieved excellence in careers outside of academia.


Role Statement
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In their role as ANU academic level B in the Research School of Computer Science the appointee will be expected to:

1. Undertake independent research in the area of Knowledge Graph Engineering and graph-based machine learning with a view to publishing original and innovative results in refereed journals, present research at academic seminars and at international conferences, and collaborate with other researchers at a national and/or international level.
2. Collaborate with the project team during the design phase of the project by participating and leading design thinking workshops
3. Following advice from the project partners and own initiative, seek out and obtain data that can be used for the project purposes
4. Reuse and extend where necessary an existing ontology for record storage developed in a pilot project
5. Establish the infrastructure to generate metadata as controlled-access linked data and to store the actual record in a NoSQL database with a binding mechanism between the two
6. Characterise user, preferences, past behaviour, spatial and temporal context and develop or refine existing machine learning algorithms in combination with OWL-Miner to mine and predict ontology graph pattern for record annotation
7. Assist in the preparation of research outputs, including scientific papers, reports and presentations
8. Actively seek and secure external funding including the preparation and submission of research proposals to external funding bodies.
9. Assist with supervision of research students.
10. Supervise less senior academic staff and research support staff in your research area.
11. Actively contribute to all aspects of the operation of the School.
12. Assist in outreach activities including to prospective students, research institutes, industry, government, the media and the general public.
13. Maintain high academic standards in all education, research and administration endeavours.
14. Take responsibility for their own workplace health and safety and not wilfully place at risk the health and safety of another person in the workplace.
15. Other duties as required consistent with the classification level of the position.


Candidate Profile
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Candidates should meet the following requirements:

1. A PhD in Computer Science or a related area, with a track record of independent research in the field of the Semantic Web, Ontology Engineering, Knowledge Graphs and/or graph-based machine learning as evidenced by publications in peer-reviewed journals and conferences, a record of developing and maintaining collaborations and by other measures such as awards, invitations to give talks at leading conferences etc.
2. Evidence of the ability to articulate and prosecute innovative research in the field of Knowledge Graph Engineering and a vision for the activities they will undertake at the ANU.
3. Demonstrated software engineering skills (e.g. through software published on Github or similar) with a sound knowledge of the Web technology stack. Experience in a variety of Web programming or scripting language including but not limited to Java, C++ and Python and knowledge and experience with triple stores, content negotiation, the linked data platform protocol, SPARQL, XML, Turtle, SHACL/ShEx.
4. Sound knowledge of data modelling using the Web Ontology Language.
5. Demonstrated experience in data analysis and machine learning or knowledge extraction.
6. Experience in designing, implementation and testing research prototype software.
7. Demonstrated effective interpersonal skills and verbal and written communication skills, including the ability to draft standard research papers, and an ability to consult and liaise effectively with a wide range of people from different disciplines.
8. Proven organisational skills and attention to detail, with a demonstrated ability to prioritise own workload and to work effectively both independently and as part of a team, meeting competing deadlines and delivering high-quality outcomes.
9. An ability and commitment to win bids for competitive external funding to support individual and collaborative research activities.
10. The ability to supervise and graduate high quality PhD/Masters research students
11. Excellent oral and written English language skills and a demonstrated ability to communicate and interact effectively with a variety of staff and students in a cross-disciplinary academic environment and to foster respectful and productive working relationships with staff, students and colleagues at all levels.
12. A demonstrated high-level understanding of equal opportunity principles and a commitment to the application of these policies in a University context.


Application information
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Applicants must apply online via the ANU recruitment portal and should upload the following separate documents:

A detailed curriculum vitae including a full publication list and the names and contact details of at least three referees (preferably including a current or previous supervisor). If your CV does not include referees you can complete these online when prompted in the application form.
A statement addressing the selection criteria.
A 1-2 page statement outlining your approach to coursework education and student project supervision.
A 1-2 page statement outlining your research objectives for the next 3 years if appointed.
Other documents, if required.


Australian National University
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The Australian National University is Australia’s premier university, ranked 1st in Australia and 24th in the World by the 2018/19 QS World University Rankings and 2nd in Australia and 49th in the World by the 2018/19 Times Higher Education. It is located in the nation’s capital, Canberra, with Australia’s largest urban campus (1.45 square kilometres).

ANU values diversity and inclusion and believes employment opportunities must not be limited by socio-economic background, race, religion or gender. The University actively encourages applications from women, Aboriginal and Torres Strait Islander people and candidates from culturally and linguistically diverse backgrounds. Furthermore, it is policy in the ANU College of Engineering and Computer Science to require selection panels to seek a gender balance when compiling shortlists of candidates for interview. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion


The ANU provides attractive benefits and excellent support to maintain a healthy work/life balance and offers generous remuneration benefits, including four weeks paid vacation per year, assistance with relocation expenses and 17% employer contribution to superannuation (included in the above salary figure). This also includes generous parental leave (up to 6 months paid parental leave), the possibility of flexible and part time working arrangements, a parental and aged care support program, dual career hire programs, ANU school holiday programs, and childcare facilities on campus. For more information, please visit http://hr.anu.edu.au/employment-at-anu


To enquire about this position please contact Dr Armin Haller, Research School of Computer Science at armin.haller@anu.edu.au

Received on Monday, 10 December 2018 11:10:42 UTC