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degree in atmospheric science, physics, environmental sciences, remote sensing, or a related field. Strong analytical and problem-solving skills, with interest in linking satellite data and atmospheric
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unstructured data from various sources to enable advanced visualization and insights. Applicants should have experience in data management, predictive modeling of pavements, or infrastructure analytics. In
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
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systems Strong analytical skills and interest in interdisciplinary, real-world problem solving Good communication skills in English and the ability to collaborate with diverse stakeholders You must have a
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. Familiarity with protein analytical methods. Good interpersonal and communication skills to obtain help when needed, such as learning new techniques from collaborators. Skill with molecular cloning. Experience
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methods or econometrics; - author or co-autor of a minimum number of 3 articles (type Article or Review) published în Web of Science magazines (Clarivate Analytics) indexed with absolute non-zero Article
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nanomaterials synthesis and characterization is desirable. Interest in energy storage technologies and machine learning applications in materials science. Strong analytical and problem-solving skills, and the
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, predictive modeling of pavements, or infrastructure analytics. In this PhD, you are expected to develop a systematic, future-proof framework for predicting pavement lifetime, with a strong focus on Dutch road
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, and enthusiasm for both field and greenhouse research. Strong analytical and critical thinking skills are essential. Experience with ecological experimental design and molecular techniques are a plus. A
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to native malaria vector species to transmission in study settings. You will use these analytical frameworks to investigate a range of questions about the future spread and control of this invasive vector in