Postdoc in AI models for the prediction of contrails climate impact - Hiring in process/Finished, not possible to apply

Job description

The overall purpose of this project is to develop artificial neural networks (leveraging remote sensing detection methods) for the prediction of the climate impact derived from contrails and aviation-induced cloudiness, contributing, thus, to a better understanding of the non-CO2 impact of aviation on global warming and reducing their associated uncertainties as essential steps towards green aviation. Contrails and aviation-induced cloudiness effects on climate change show significant uncertainties since they are subject to meteorological, regional, and seasonal variations.

In this context, the researcher will develop deep learning architectures to generate AI models capable of predicting the radiative forcing of contrails based on data-archive numerical weather forecasts and historical traffic. We will make use of Convolutional Neural Networks (CNNs), together with transfer learning from already-existing models, as well as recurrent networks such as Long-Short Terms Memory (LSTM), and generative models such as Generative Adversarial Networks (GANs) and variational autoencoders (VAEs). The methodology will follow two steps: temporal predictions and spatial predictions. Finally, the developed AI-driven models should predict, 24 hours in advance, the climate impact of contrails and aviation-induced cloudiness with 80-90% accuracy.

What we offer

• A position at a leading technical university that generates knowledge and skills for a sustainable future
• Engaged and ambitious colleagues along with a creative, international and dynamic working environment
• Work in Stockholm, in close proximity to nature
• Help to relocate and be settled in Sweden and at KTH

Read more about what it is like to work at KTH

Qualifications

Requirements

•  A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made
• Proficient in the English language as this will be required in day-to-day work
• Relevant published work in the field of aerospace
• Applicants must possess the ability to work independently and perform critical analysis as well as possessing good levels of cooperative and communicative abilities. 

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• A suitable background for this position would be a PhD (completed in the last five years) in Mechanical/Aerospace Engineering or Computer Science with a specialization in computational modelling
• Research expertise
• Teaching abilities
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality International experience
• A relevant degree project

Great emphasis will be placed on personal competency.

Trade union representatives

You will find contact information to trade union representatives at KTH's webbpage.

Application

Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.

The application must include:

• Statement of professional interest.
• CV with list of publications.
• Transcripts from university/university college.
• Contact information for at least two references.
• PhD thesis and two selected scientific papers (in pdf format).

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The position offered is for, at the most, two years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.

Others

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.