Postdoc in machine learning for time series analysis - Hiring in process/Finished, not possible to apply

Job description

Machine learning methods are solving a wide range of practical problems but is not always clear how this impressive performance is obtained. This becomes problematic when applying such methods to sensitive tasks with the potential for serious real-world consequencies, such as in finance and medicine.

This postdoc will develop explainable machine learning methods for financial time series and medical data. The work will draw on scattering transforms (a convolutional neural network with fixed weights) and principal component analysis from partial measurements, tools which achieve state-of-the-art performance on various tasks yet are structured enough to enable theoretical analysis. The expected outcome of the project is the development of powerful new data-driven methods for time series analysis with an accompanying theoretical framework.

This postdoc is part of a larger project within the Department of Mathematics at KTH whose goal is to explore and exploit recent developments in machine learning and artificial intelligence to solve problems in financial mathematics. As such, the postdoc will include close collaboration with other members of the department but also internationally.

For more information, see.

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
• Works 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, obtained within the last three years prior to the application deadline (With some exceptions for special reasons such as periods of sick or parental leave, kindly indicate if such reason exists in your resume).
• Research expertise
• Experience with machine learning methods
• Creativity
• Independence
• Collaborative abilities

Preferred qualifications

• Knowledge and experience of deep learning frameworks, such as PyTorch or TensorFlow
• Teaching abilities
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

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:

• CV including relevant professional experience and knowledge.
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
• Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.

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.