- Development of methods to precisely determine the expected energy yields of planned wind farms
- Development of AI-based and data-driven methods to solve key problems in wind farm planning and site assessment Improving the simulation and estimation of wind conditions at complex locations by combining AI approaches with CFD simulationsReduction of uncertainties related to short-term wind measurements or incomplete measurement data at planned wind farm sites
- Analysis of wind measurement and weather model data, ., with regard to correlations or patterns in the data
- Implementation of efficient data pipelines for scientific analyses and for training models
- Evaluation and estimation of uncertainties of the developed methods in their use for investment decisions
- Communication of the results to partners from the wind energy industry and research
- Scientific collaboration in the above-mentioned project
- Preparation of scientific publications and conference papers based on the results
- Completed course of academic study (Master degree) within the field of data science, mathematics, computer science, physics, meteorology or a related natural science or engineering degree with at least a good grade. The required degree must be available by the recruitment date at the latest. The degree required for this position must have been obtained by the starting date at the latest.
- Interest in scientific work in the field of wind energy, in particular site assessment of wind turbines
- Programming skills, ideally with Python
- Goal-orientated thinking, strong analytical skills, team spirit
- Independence, initiative and enjoyment of interdisciplinary collaboration
- Knowledge in the field of energy meteorology
- Knowledge in the field of wind energy
- Knowledge in the field of machine learning/artificial intelligence
- Very good knowledge of German and/or English
- The position is designed for further scientific development and is supported accordingly. This is associated with very good opportunities for a doctorate or further scientific development after a PhD
- Possibility to realise your own ideas within the framework of the research project topic
- Close cooperation with the Fraunhofer Institute for Energy Economics and Energy System Technology (Fraunhofer IEE) as well as further research and industry partners in the field of wind energy
- Supervision of the scientific work by experienced scientists at Fraunhofer IEE, as well as integration into the research team "Site Assessment Wind" at Fraunhofer IEE
- Flexible working hours and the option to work from home enable a good work-life balance
- you will be offered an interesting and diverse range of tasks within the framework of a modern and ambitious university,
- you will be part of an interdisciplinary team with a good and collegial working atmosphere,
- you will have the opportunity to participate in professional and interdisciplinary further education measures,
- is your workplace with good connections to public transport, which you can currently use free of charge.
- an additional company pension (VBL),
- an optional child supplement in accordance with TV-Hessen, a family-friendly university (including childcare for emergencies),
- an annual bonus
- an entitlement to capital-accumulation benefits,
- a promotion of voluntary commitment,
- low-cost participation in university sports and a full range of fitness activities as part of Unifit, as well as workplace health management
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Research Assistant - Kassel, Deutschland - Universität Kassel
Beschreibung
The University of Kassel is a modern and growing University with round about students. The university's wide range of expertise covers subjects in the natural, applied, cultural and social sciences.
The following position is to be filled as soon as possible in the Department of Electrical Engineering/Computer Science, Institute of Electrical Engineering - Department of System Operation (Prof. Dr.-Ing. Martin Braun)
Research Assistant (m/w/d), EG 13 TV-H, fixed-term, full-time (currently 40 hours per week)
Application deadline:Date of hire:
as soon as possible
vacancy number: 37252Full-time or part-time with 50% to 100% of the regular working hours of a full-time employee. The position is initially limited until 31 May 2026 as part of the project "STRAIGHT - Increasing quality and efficiency in yield estimation for wind farms" in accordance with § 2 (2) WissZeitVG. The possibility of a doctorate is given.
Would you like to advance the energy transition and are you interested in programming and artificial intelligence? The project "STRAIGHT - Increasing quality and efficiency in yield estimation for wind farms" offers an ideal opportunity to do so.
The primary aim of the research project is to accelerate wind farm planning through digitalisation and data-driven models in order to support the expansion of wind energy. Methods using artificial intelligence developed and adapted to meet the objectives of the project.
Tasks:
Requirements:
Advantages are:
We offer:
Our Offer:
As an employee of the University of Kassel
In addition, you will benefit from the advantages of employment in the public service such as:
You can find more jobs at
In exceptional cases, we will also accept your application documents in paper form addressed to: The President of the University of Kassel, 34109 Kassel, Germany, or via mail to
Information and FAQ about applying for a job offer:
The University of Kassel is very interested in the professional satisfaction of its employees. It is distinguished as a family-friendly university and, in the interests of equal opportunities, strives to offer everyone the same opportunities for development and to counteract existing disadvantages. It promotes the Family Welcome Service and also the Dual Career Service for positions that are scientifically and academically filled. One of the strategic goals of the University of Kassel is to significantly increase the proportion of women in research and teaching. Applications from women are therefore particularly welcome. Seriously handicapped and equivalent applicants are given preference if they have the same suitability, qualifications and professional performance. Full-time positions are generally divisible (except when filling civil servant positions). Applications indicating the Position Number, which may be in digital form, should be sent to the President of the University of Kassel, 34109 Kassel, Germany quoting the applicable reference number.