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VACANCY: Post Doctoral Researcher in Computational Social Science

TITLE OF POST: Post Doctoral Researcher in Computational Social Science

LOCATION: MACSI at University of Limerick

SALARY SCALE: €37,874 - €49,048 p.a. pro rata

Informal queries: Prof James Gleeson

Further information for applicants and application material is available online from: http://www.ul.ie/hrvacancies/

CONTRACT TYPE: Specific Purpose

JOB DESCRIPTION

QUALIFICATIONS:

  • Doctoral degree (level 10 NFQ) completed or near completion, in mathematics, applied mathematics, or other relevant discipline with significant mathematical content.

 

OVERALL PURPOSE OF THE JOB:

The Mathematics Applications Consortium for Science and Industry (MACSI) is Ireland’s largest applied and industrial mathematics group and works closely with scientists and industrial companies across a wide variety of sectors. MACSI’s aim is to foster new collaborative research, in particular on problems that arise in industry through the application of cutting-edge mathematical and modelling techniques.

 

The emerging discipline of Computational Social Science (CSS) studies human behaviour, as manifested in the digital trails we leave in our interactions with each other. The development of mathematical models for CSS is urgently required to underpin the analysis of large-scale data, and to move beyond the identification of correlations to create new scientific understanding of collective behaviour in both online and offline social networks.

 

In this Science Foundation Ireland funded project we are seeking to recruit a Post Doctoral Researcher to join Professor James Gleeson’s team in the development new mathematical techniques and models to help revolutionise the understanding of the dynamics of social spreading phenomena, such as viral information contagion and cascades of popularity. We will focus on the mathematics of age-dependent (non-Markovian) branching processes to generate analytical and asymptotic results for inference and calibration with large-scale CSS data. Understanding and controlling the temporal aspects of information diffusion and cascade dynamics on social networks will improve the predictability of technology adoption and opinion propagation, and enable us to accurately identify the most influential nodes within diverse dynamical systems on complex networks. Our algorithms will be applicable to online marketers, mobile phone networks, and in cases where widespread broadcasting public-interest information is urgent (e.g., health or terrorism alerts, missing-person searches, disaster relief).

 

Responsibilities

 

Research

  • Contribute to the research programme of MACSI under general guidance of a Principal Investigator.
  • Define research objectives and proposals for own (or joint) research in line with research strategy.

 

Research Management

  • Plan, co-ordinate and implement research project (this may include managing a small research team/co-ordinating other researcher activity).

 

Income Generation/Funding

  • May identify sources of funding and pursue the process of securing funds.
  • May work with PI to contribute to proposals for developmental purposes. 

 

Research Outputs - Write Up and Dissemination

  • Write up results from own research activity.
  • Contribute to the research project’s dissemination, in whatever form (report, papers etc.).
  • Present information on research progress and outcomes e.g. to funding bodies; conferences, steering groups; other team members, as agreed with the PI.
  • Where appropriate, work with PI to register patents to protect intellectual property.

 

Supervision

  • May act as co-supervisor or be a member of a supervision panel.
  • May act as mentor to foreign students on undergraduate placement.

 

Essential Criteria

  • Doctoral degree (level 10 NFQ) completed or near completion, in mathematics, applied mathematics, or other relevant discipline with significant mathematical content.
  • Highly proficiency in the use of at least one high-level computing language (e.g., MATLAB, Python etc.).
  • Well-developed ability to communicate technical concepts to non-experts.
  • Ability to liaise and collaborate with other researchers in the University and Industrial clients.

                                                           

Desirable Criteria

  • Experience in developing mathematical models for social spreading phenomena.
  • Publications on the mathematics of networks.
  • Demonstrated strong organisational skills.
  • Evidence of participation in interdisciplinary research projects.
  • Experience of industrial research & development and be fully aware of the importance of intellectual property management and protection.

 

 

 


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