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Field
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service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. The successful candidate should have a PhD in terrestrial ecology
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participating in projects that collect and utilize agronomic data from forages and crop rotations, and (3) writing scientific publications and grant applications. Qualifications: Required: A PhD degree in a
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manipulation, and metasurfaces. Who we are looking for We seek candidates with the following qualifications: The applicant should have a PhD degree in physics, optics, nanoscience, or a related subject area. The
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Department of Chemistry and Chemical Engineering , contributing to a highly interdisciplinary research setting. We seek candidates with the following qualifications: PhD in materials science, physics, polymer
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. The successful candidate will work on cutting-edge projects involving artificial intelligence (AI) and computational pathology, with a particular focus on developing and applying machine learning algorithms
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these datasets to detect chromosomal abnormalities and study their breakpoints. Using statistical methods and machine learning, we will explore how these structural variants arise and which recurring structures
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, genotyping, immunohistochemistry, RNA in situ hybridization and statistical analyses. Qualifications The ideal candidate should have a PhD in molecular or developmental biology, neurosciences, photoreceptor
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such as epidemiology, biostatistics, computer science, statistics, etc. We will also consider those with PhDs in other areas but who have advanced/relevant data science skills (e.g., machine learning
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psychiatry. The projects will involve advanced epidemiology, pharmacoepidemiology, and machine learning methods. You will be part of a well-funded and successful research group, collaborating with
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and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The tasks include primarily leading and conducting research