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. The PhD student will be enrolled in a doctoral programme of Chalmers and is jointly supervised by supervisors from the academic and industry sectors. Further information can be obtained by contacting Docent
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implementation. About the project Reactive synthesis refers to the automatic generation of programs from high-level behavioral specifications. This approach plays an increasingly important role in areas such as
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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performance are expected. Required qualifications: Proficiency in programming (primarily Python or MATLAB) Strong communication and collaboration skills, including the ability to work across research groups and
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. Good skills in programming (e.g. Matlab, Python, C/C++) Strong written and verbal communication skills in English The following experience will strengthen your application: Experience with radars
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). The successful candidate will work in Maximilian Larena’s research group, and co-supervised by Prof. Mattias Jakobsson and Prof. Carina Schlebusch. The research program consists of an international team
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Administration, Entrepreneurship section, at Umeå School of Business, Economics and Statistics with Prof. Norbert Steigenberger as your main supervisor. With this PhD project, funded by Lundbergs Foundation, we
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for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in English The
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and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create
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project under supervision of experienced researchers and following an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research