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Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via

Job advertisement PhD Position: Solar and PV forecasting with neural networks BFH/ETH

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European Geosciences Union

PhD Position: Solar and PV forecasting with neural networks BFH/ETH

PhD Position: Solar and PV forecasting with neural networks BFH/ETH


Bern University of Applied Sciences




Relevant divisions
Atmospheric Sciences (AS)
Earth and Space Science Informatics (ESSI)

Full time

Entry level


Required education

Application deadline
Open until the position is filled

16 August 2021

Job description

PhD Position: PV forecasting with neural networks BFH/ETH
100 % / Limited for 4 years / Biel / Start by arrangement

What you’ll be doing here

Conduct doctoral research at Bern University of Applied Sciences and ETH Zurich Develop an optical-flow machine-learning framework for short-term prediction of the solar resource and the photovoltaic power generation with lead times of up to several hours Combine ground and satellite measurements to validate the developed machine learning framework and estimate associated uncertainties Work in a stimulating research environment, and present and publish your results in high-profile journals and conferences Bern University of Applied Sciences and ETH Zurich are leading universities in science and technology renowned for excellent research, education, and cutting-edge innovation

What you’ll bring with you

Master degree in Computer Science, Computer Vision, Machine Learning, Statistics, Engineering, Atmospheric/Climate Science, Physics, or a related field Strong background in machine learning and excellent analytical skills; Excellent programming skills, proficiency in Python; Proficiency in written and spoken English Good proficiency in state-of-the-art libraries for machine learning or computer vision; highly motivated demonstrate strong ambition for excellence and enthusiasm for research Please include your CV, copy of master thesis, academic transcript incl. list of completed courses, contact details of two referees; and a brief description of your project idea (max. 2 pages) that relates to your experience and the relevant literature

And here are even more good reasons to opt for BFH

Plenty of contact with eager young people from all over the world who are set on achieving things. Great freedom in work organisation with lots of leeway for your ideas, your creativity and decisiveness. Focus on research that is geared towards practical orientation and the education of committed people rather than mere profit maximisation. Work place in prime location with excellent access. National and international networks and contacts with business, economy, society and the political world.

Apply now
Department of Engineering and Information Technology
In the Department of Engineering and Information Technology we don’t move with the times, mostly we are a bit ahead of them! We find it fascinating what benefits technology can have in people’s everyday lives. We gain knowledge through research and joint projects with industry and business. This exchange brings about cutting-edge insights that we continually share with students.

How to apply

To apply, please submit your complete application documents through our online job portal, accessible via