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Innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts: Algorithms for multimodal data-based inference and prediction for climate science applications

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  • Full or part time
    Prof M Rodrigues
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Anthropogenic climate change is one of the most urgent problems facing mankind. To avoid dangerous levels of global warming, the UN Conference of Parties 2015 in Paris reached a historic agreement to keep global mean temperature rise “well below” 2°C above pre-industrial levels. Anthropogenic aerosols have most likely offset some of the greenhouse warming to date, particularly through their interaction with clouds, however, despite decades of intensive research, significant uncertainties in the magnitude of this cooling still persist.

Even though big datasets have been widely analysed to advance our understanding of aerosol-cloud climate interactions, many uncertainties remain and current methods are often inadequate, Artificial intelligence (AI) and machine learning, which are already revolutionising many areas of research, have not yet been fully applied in climate science – and scientists are not trained adequately. iMIRACLI proposes that merging of AI, machine learning and climate science will deliver a breakthrough in our understanding of the impact of aerosol-cloud interactions on climate.

Our innovative training plan will match each PhD student with supervisors from climate and data science backgrounds, as well as non-academic partners, across Europe and provide them with training in both state-of-the-art data and climate science techniques producing a new generation of climate data experts.

The Role
The ESR will be enrolled on the PhD programme at UCL’s EEE Department and will write his/her thesis on a topic related to Algorithms for multimodal data-based inference and prediction for climate science applications, supervised by Prof. Miguel Rodrigues at UCL and co-supervised by members of the other academic/industrial teams during the secondments.

Objectives
This project will develop new multimodal deep learning algorithms that are able to capture the relationship between diverse data and image modalities – such as infrared image information, hyperspectral infrared sounding information or active remote sensing – in order to deliver relevant insights in outstanding climate science challenges such as aerosol-cloud-precipitation-climate interactions.

The project will also develop robust deep learning algorithms that are able to deal with a number of issues arising in the climate science domain such as: i) uncertainty in the testing/training data, ii) different degrees of uncertainty in different data modalities, and iii) small data. The algorithms will also be applied to real data to determine historical auto-conversation rates from actual satellite observations. These novel observations are critical to evaluate the representation of precipitation

Expected results
• New multimodal deep learning algorithms algorithms
• New machine learning approaches to deal with data uncertainity
• New machine learning approaches to deal with small data
Planned secondment(s): 3 months at University of Leipzig, 3 months at the MetOffice InformaticsLab Training: wide ranging programme – full details in job description.
The ESR’s PhD must be designed and conceived as an integral part of the overall iMIRACLI project. The successful candidate will be a team player, prepared to work closely with the Project’s senior staff and other ESRs.
This is an outstanding opportunity to be part of a network of leading scholars working on the state of the art in Data Science and Climate Science.
The ESR will help organise and present their research at a major international conference on the themes of the iMIRACLI research programme.

Duties & Responsibilities
1. Undertake postgraduate research in support of the agreed doctoral research project.
2. Work closely with the academic supervisors to ensure the compatibility of the individual project with the overall goals of iMIRACLI.
3. Present and publish research to both academic and non-academic audiences.
4. Attend and participate in academic and non-academic conferences, events and seminars.
5. Actively participate in outreach activities and in promoting the Project’s progress and events in social networks.
6. Attend and participate in all training events and supervisory meetings.
7. Be seconded to other network partners as necessary to fulfil the grant obligations.
8. Prepare progress reports and similar documents on research for funding bodies, as required.
9. Contribute to the delivery and management of the wider Programme, including attending and participating in programme committee meetings.
As job descriptions cannot be exhaustive, the ESR may be required to undertake other duties, which are broadly in line with the above duties responsibilities.

Person Specification
Essential
1. A good Undergraduate degree and a postgraduate Master’s degree (or equivalent) in electronic or electrical engineering, computer science, mathematics or a physical sciences subject.
2. Highly proficient English language skills.
3. Ability to think logically, create solutions and make informed decisions.
4. Willingness to work collaboratively in a research environment.
5. Ability to travel and work across Europe.
Desirable
1. Excellent written and verbal communication, including presentation skills.
2. Excellent organisational skills, attention to detail and the ability to meet deadlines.
3. A strong commitment to your own continuous professional development.

How to apply
Applications must be must submitted online to www.ucl.ac.uk/hr/jobs . Reference 1866611
Only two supporting document files can be submitted. Please combine documents before uploading.

The application must include:
a) Curriculum vitae
b) Academic transcripts
c) Letter outlining your motivation, skills and fit for the programme (no more than 2 pages)
d) Three reference letters, one of whom should be from a recent academic supervisor. The referees must e-mail their recommendations directly to [Email Address Removed] .

Further Information
For full details on the eligibility requirements and the selection process, please see the job description which can be downloaded from:
https://www.ucl.ac.uk/electronic-electrical-engineering/vacancies
For more information about the post, please contact: [Email Address Removed] or [Email Address Removed]

Funding Notes

Between £37,730 and £46,950 gross per annum at the current rate of exchange.
These figures are before employer and employee deductions, including tax, national insurance and pension contributions, subject to the pension choices of the appointee.
The level of salary is also subject to the family status of the appointee as to whether they qualify for a family allowance. Due to potential future changes in the Euro/Pound Sterling exchange rate over the period of the appointment, where amendments are required, corrective payments will be made.
Salaries are not subject to either cost-of-living adjustments or increment progression, and are inclusive of London Allowance.



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