Posted to IASSIST on: 2017-06-11
Employer: University of Essex
Employer URL: http://www.essex.ac.uk/
Description
The Institute for Analytics and Data Science (IADS) seeks to appoint a full-time Postdoctoral Research Fellow to start on or after 1 August 2017 to support the Institute’s work in analytics, data science and Big Data. On successful completion of the Fellowship and probation period, the Research Fellow will be appointed to a permanent Lecturer post in the School of Computer Science and Electronic Engineering.
We wish to add to the Institute’s capability to undertake world class research and development work as well as open up and develop new research activities in this area that will become recognized as outstanding and internationally leading. We seek highly motivated, enthusiastic and professional candidates who have excellent knowledge of computer science, artificial intelligence, machine learning or text analytics, and possess strong software engineering and programming skills in high level programming languages such Java, C, Perl and Python. Particular research areas of interest include but are not limited to:
- machine learning;
- reinforcement learning, neural networks, deep learning;
- data mining;
- predictive analytics;
- natural language processing and advanced text analytics;
- semantic information extraction and the Semantic Web;
- social media analysis;
- handling of data in motion (multi-stream processing and reasoning, complex event processing and reasoning);
- decision support tools and systems.
The Fellowship is for a fixed term because it is for a period of career development. During the period of the Fellowship, the Research Fellow will be on a probation period of three years. To enable the Fellow to meet the requirements of probation, and to provide a good foundation in higher education practice for the Fellow’s ongoing career, they will be allocated a limited amount of teaching and supervision in the School of Computer Science and Electronic Engineering.
Duties of the Post:
- Undertake Foundational and Applied Research: to undertake high quality independent and collaborative research that meets Research Excellence Framework (REF) standards within the Institute for Analytics and Data Science. This could include, but not be limited to:
- Develop research objectives and proposals;
- Use new research techniques and methods and use initiative and creativity to identify areas of research and new research methods;
- Use creativity to analyse and interpret the research data and draw conclusions of the outcomes;
- Author and co-author research papers;
- Develop and undertake applied research in collaboration with businesses and other stakeholders;
- Attendance and contributions (presentations) to annual international conferences;
- General project management and coordination;
Foster links and collaboration with appropriate internal and external research groups working on similar themes.
- Contribute to Public Engagement & Impact: to explore all appropriate contributions to impact and engagement activities, such as community engagement and interactions with other public sector bodies, business and the third sector.
- Develop Interdisciplinary Collaborations within IADS: to take an active role in facilitating and catalysing collaboration across disciplinary boundaries within the Institute for Analytics and Data Science. The Fellow will be working with the Director of IADS and using their initiative in developing a distinctive and inspiring collaboration across academic departments and research centres.
- Support the Research Culture of the Institute for Analytics and Data Science: to actively participate in the Institute’s workshops and seminars.
- Apply for Grants: To identify appropriate sources of external funding, write and contribute to bids for research and/or enterprise related work working together with the Director of IADS and other researchers.
- Supervise Students: To work with the Director of IADS and other researchers in identifying projects for suitably qualified applicants across big data and analytics, recruiting candidates, and being part of the supervisory team for them.
- Support IADS Administratively: to contribute fully to the Institute for Analytics and Data Science and institution by playing a role in working groups, committees and other activities;
- Teaching: a limited amount of teaching, as appropriate to a research-based post, to enable the candidate to meet the requirements of probation, and to provide a good foundation in higher education practice for the Fellow’s ongoing career.
- Other Duties: Such other duties, commensurate with the grading of the post that may be assigned by the Director of the Institute for Analytics and Data Science or their nominee.
Essential:
- PhD in Computer Science, Artificial Intelligence, Data Science, Statistics, Computer Engineering or related discipline
- Publication of research that meets the criteria for submission to the Research Excellence Framework
- Experience of or demonstrable potential to teach undergraduate and postgraduate students
- Excellent knowledge of computer science, artificial intelligence, machine learning or text analytics, and possess strong software engineering and programming skills in high level programming languages such Java, C, Perl and Python
- Excellent demonstrable communication and presentation skills
- Excellent time management, organisational and project management skills
- Excellent interpersonal skills, and ability to inspire, connect, network and collaborate
- Strong software engineering skills and programming experience
- Excellent IT skills
- Commitment to student support and guidance
- Ability to work effectively and positively, both independently and as part of a team, together with a commitment to collaborative working, particularly across disciplinary boundaries
- Possession of coherent research plan for the future
- Potential to innovate in their research field and to attract research grant funding
- Potential for research to have impact outside of the academic world
Desired:
- Postdoctoral research experience
- Evidence of successful participation and contribution to interdisciplinary and national/international collaborations
- Experience of contributing to the preparation of successful bids for external funding
- Experience of interacting with non-academic sectors through impact activities or public engagement (research)
- Experience of running and contributing to workshops, symposia and conferences
- Experience of successful supervision of PhD students to completion
- Experience in supervising undergraduates and postgraduates
- Ability to identify new opportunities for collaborations that contribute towards the objectives of the Institute for Analytics and Data Science
Archived on: 2017-07-10