Research Modeller (Research Officer) (Temporary) (# of pos: 2)

Duration:

Two temporary funded contract posts, the indicative duration of which is 24 months, subject to contract.  A panel may be formed from which future similar vacancies may be filled; such a panel will remain active for a maximum period of 12 months.

Basic Function    

This competition seeks to recruit two contract research officers focused on modelling the impact of management on ecosystem carbon flows and changes in soil organic carbon (SOC). The appointees will join a well-resourced team of permanent and contract staff investigating the quantification of ecosystem C fluxes at a variety of scales and using various techniques. There will be a large range of datasets for model constrain and validation. They will conduct model refinement, including the incorporation of new grass growth modelling into biogeochemical models which will improve our understanding of the impact of soil type and land-use management practice on carbon sequestration. These positions will join the GHG and spatial analysis scientific group of Teagasc and will be based at Johnstown Castle and Ashtown.

Background

Terrain-AI (T-AI) is a collaborative research project coordinated by Maynooth University, and supported by Science Foundation Ireland’s Strategic Partnership Programme involving Teagasc, TCD, UCD, UL and DCU together with primary Industry partner Microsoft. T-AI’s core R&D activity revolves around improving our knowledge and understanding of Land Use activity - as this relates to Climate Change. MACSUR is a FACCE-JPI project investigating how biogeochemical modelling of agricultural ecosystems can better inform environmental and climate change policy.  Expanding global populations, agricultural intensification and climate change are increasing pressures on natural and managed environments. To maximise sustainable land use, it is essential that we develop tools and information services that can inform more effective and sustainable management practices. The objective of this research is to integrate a national network of benchmark test-sites and a digital data platform capable of integrating, analysing and visualising large volumes of Earth observation data-streams, including data from satellites, drones and on-site measurements and integrating these datasets into appropriate modelling approaches to simulate greenhouse gas fluxes, sources and sinks. The overall aim of both T-AI and MACSUR is to increase our understanding of how management practices can influence carbon emissions arising from the landscape, thus enabling more sustainable land management within environmental and regulatory constraints.

• To model the impact of management on ecosystem carbon (and nitrogen) cycling using an ensemble of ecosystem and soil biogeochemical models (eg. DNDC, DAYCENT, RothC, ECOSSE).

• To improve model architecture via linkage to grass growth models.

• To publish findings in peer-reviewed publications

• To contribute to the teamwork and team-spirit in the agri-environmental research department at Johnstown Castle, and to foster and add to further collaboration and integration.

• To assist Teagasc in meeting the commitments of the Quality Customer Service Charter and Action Plan.

• To actively participate in the annual business planning and Performance Management Development System (PMDS) processes.

• Carry out such other duties as may be assigned from time to time.

• Fully co-operate with the provisions made for ensuring the health, safety and welfare of themselves, fellow staff and non-Teagasc staff and co-operate with management in enabling Teagasc to comply with legal obligations. This includes full compliance with the responsibilities outlined in the Safety Statement.

* This job specification is intended as a guide to the general range of duties and is intended to be neither definitive nor restrictive.  It will be reviewed from time to time with the post-holder.

Essential

Desirable

Qualifications

• Candidates must have a QQI Honours Level 8 degree in computer science, mathematics, agricultural science, environmental science or environmental policy.

• Postgraduate degree in environmental science, soil science, environmental policy or environmental modelling.

Skills

• Good working knowledge of programming languages (C++, Python, R).

• Ability to synthesis knowledge through literature review.

• Proven ability to write concise reports

• Good one-to-one and group communication skills.  

• Experience in modelling environmental processes

• Knowledge of livestock agricultural systems

Knowledge

• Good knowledge of soil carbon and nitrogen cycling in agricultural systems

• Understanding of Irish agricultural systems.

• Understanding of EU and national GHG policy

• Understanding of knowledge transfer, communication and outreach strategies.

Behavioural Competencies

• Ability to work independently if necessary, and meet self-imposed milestones and deliverables.

• Ability to lead group discussions/workshops with a range of stakeholders including scientists, public servants, farmers and other stakeholders.

• Willingness to collaborate positively within the programme team as well as with outside agencies.

• Ability to align personal development objectives within the programme objectives.

• Strives for high quality of work and demonstrates commitment to the programme.

• Ability to communicate effectively to enable knowledge and technology transfer.

Other

As this role may involve travel within EU, candidates must satisfy and continue to satisfy during employment with Teagasc, legal requirements to gain entry to other EU countries

Eligibility

This is an open public competition. Should a current serving Teagasc staff member be successful in their application through open public competition for this post, their current contract of employment with Teagasc will come to an end on taking up this post.

 Note:  The ‘essential’ qualifications, knowledge, skills and behavioural competencies outlined above are ‘must-have’ which will be used in the selection process.