12418- Integrated assessment modelling

Milano, Italy, Italy

Full Time

SEME

Mid Level

Job Opening cod. 12418

CMCC Position

Integrated assessment modelling

(Deadline: December 31, 2023)

The CMCC Foundation is a scientific research center on climate change and its interactions with the environment, the society, the world of business and policy makers.

Our work aims to stimulate sustainable growth, protect the environment and develop strategies for the adaptation and mitigation of climate change.

Our Division of Sustainable Earth Modelling Economics (SEME) is looking for new position of bright researchers motivated to work on the defining issue of climate change. Due to an expanded portfolio of projects and our belief in multi/disciplinarity, we are promoting a cluster hiring consisting of several job opportunities in several areas of climate research. These include applied and behavioural economics, political economy, data science, decision theory, and energy-economy-climate modelling (see below for specific job ad). The cluster hire is intended to strengthen our existing research groups and promote new research lines. It is mainly targeted at post-docs and junior researchers (though other seniorities will be considered).

For this position of “Integrated assessment modelling” we are encouraging applications by modellers and economists interested in integrated assessment modelling for climate change. The candidate will join an international and interdisciplinary team to contribute to developing our suite of integrated assessment models, which include detailed-process climate-energy-economy models, energy system models and macro-economic models. The successful applicant will work on a model development project, investigating climate change solutions and improving the representation of climate change mitigation and impacts in our models. Specific tasks included but are not limited to:

Integration of climate change adaptation and impacts into climate-economy models at regional and national level;
Developing methods to represent biodiversity and ecosystems in integrated assessment models;
Capturing the resources and material requirements of the low-carbon transition;
Contribution to developing the open-source integrated assessment models WITCH and RICE+;
Write and contribute to scientific articles and science-policy reports derived from the above work, and present those at scientific workshops and conferences.

The job location is CMCC Division in Milan, Italy.

We are looking for a motivated person with the following requirements:

PhD in economics, applied mathematics, environmental engineering, or any related fields to integrated assessment models;
Modelling experience using modelling language (GAMS, AMPL, JUMP) and fluency in programming language such as python, julia or R;
Fluency in English (Italian not needed), good presentation and writing skills;
Willingness to travel to project meetings and to conferences;
Ability to work in an interdisciplinary and diverse environment committed to high-quality research;
Desirable: Experience with integrated assessment modelling.

Belonging to legally protected categories (ex L. 68/99) will constitute a preferential condition.

Some fiscal benefit could be applied for repatriated workers or foreign researchers/professors, having the requirements defined by Dlgs 147/2015 (for repatriates) or Dl 78/2010 (for foreigners).

The appointment period will be initially 24 months, renewable for two additional years pending a positive evaluation. Tenure can be granted from 2 to 4 years after being appointed as a junior researcher.

The gross salary will be based on qualification and working experience and competitive with major research centers in Europe.

This job announcement is a public invitation to express interest for the above mentioned CMCC Position.

Applicants responding to this posting declare that they have read, understood and agreed to the “Official Rule for the CMCC Personnel recruitment".

We will keep your information on file for up to 1 year.

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12418- Integrated assessment modelling

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