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Field
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for the facility's methodological development, including the supervision of researchers in these projects Requirements PhD in Physics, Engineering, Neuroscience or a related field Prior experience with OPMEG, SQUID
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* Integration in interdisciplinary and multi-institutional networks * Excellent scientific infrastructure and mentoring We are looking for: * Curious mind-set with a strong interest in the physics and engineering
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Analyst / Bioinformatician (f/d/m) Start date:October 1, 2026 With us, you will work on exciting projects, contribute your own ideas, and develop innovative solutions at the interface of data, technology
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solutions for real security and data protection issues. The Secure Software Engineering research department researches and develops innovative solutions for the automatic identification of malware
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(Master’s degree) in Physics, Engineering, or a related field. Expertise in at least one of the following areas: adaptive optics, laser communications, high-energy lasers, atmospheric turbulence, or optical
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learn and work with new tools and programming languages Willingness to undertake national and international business travel, particularly within Europe You are passionate about technology and research
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, computer science, natural sciences and engineering. Who can apply? The scholarship programme is aimed at high-achieving students from developing and emerging countries who would like to complete a Master’s degree in
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or equivalent (e.g. geoecology, engineering biology, environmental sciences, water sciences). Desirable: - good background in hydrogeology with experiences in geological field work, hydrochemical and
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Master's degree (or equivalent) in physics, chemistry, electrical engineering, materials science, or others. IDEAS recruits excellent PhD candidates at the interface of data science and environmental & life
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sedimentological (grain size distribution), geochemical (XRF, ICP-OES, C/N), and soil physical (density, pore volume, water conductivity) analyses in the laboratory, multivariate statistical evaluation of the data