15 PhD studentships in Innovative Training Network iMIRACLI on machine learning in climate science

Updated: 8 months ago
Deadline: 02 Feb 2020

iMIRACLI Innovative Training Network (ITN)

15 PhD studentships to work with leading climate and machine learning scientists across Europe to tackle the issue of aerosol-cloud interactions

Admissions open now

iMIRACLI (innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts) brings together leading climate and machine learning scientists across Europe with non-academic partners to educate a new generation of climate data scientists.

This EU funded Marie Skłodowska-Curie Innovative Training Network (ITN) will fund 15 PhD students across Europe. They will develop maching learning solutions to deliver a breakthrough in climate research, by tracing and quantifying the impact of aerosol-cloud interactions from the microscale to large-scale climate.

Each student will have an interdisciplinary supervisory team, combining academic climate and machine learning supervisors as well as a non-academic advisor. International secondments to co-supervisors as well as to the non-academic partners will enrich student experience and training. 

Academic hosts: Universities of Oxford, Leipzig, Stockholm, ETH Zurich, Edinburgh, Valencia, UCL London, German Aerospace Centre DLR, EPFL Lausanne with partners Iris.ai, FastOpt, MetOffice, Alan Turing Institute, Amazon, GAF, University of Jena. 

PhD students will begin their projects in September 2020, kicking off with a summer school held at Oxford. 

Candidates must be Early-Stage Researchers (in the first four years of their research careers and not yet have been awarded a doctoral degree) and are required to undertake transnational mobility (move from one country to another). 

Applications for studentships are open now, with an application deadline of 3 February 2020. All applications must be submitted through the iMIRACLI project webpage: 


This project receives funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No 860100.

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