QUALIFICATIONS:

• A doctoral degree (level 10 NFQ) completed  in applied mathematics, mathematics, physics, computer science, or other relevant discipline

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 two postdoctoral researchers to develop 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. As part of the project, we will seek to develop and apply algorithms to social spreading phenomena that are of interest to industry partners.

The candidate should have a strong publication record in either or both of the following areas:

• Mathematics of networks.
• Analysis and model calibration using large-scale Computational Social Science data.

DESCRIPTION:

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

• A doctoral degree (level 10 NFQ) completed in applied mathematics, mathematics, physics, computer science, or other relevant discipline.
• Strong publication record in either or both of the following areas:
  • mathematics of networks.
  • analysis and model calibration using large-scale Computational Social Science data.
• High 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 with industrial partners.
• Excellent interpersonal and communication skills.

Desirable Criteria

• Experience in developing mathematical models for social spreading phenomena.
• Demonstrated strong organisational skills and ability to lead within a group.
• Evidence of participation in interdisciplinary research projects.
• Experience of Industrial Research & Development and awareness of the importance of Intellectual Property management and protection.