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Postdoc position in method development in human statistical genetics, with a focus on classificat...
on a predictor X; candidates should understand how this function performs the analysis (e.g., estimates the effect size, assesses significance). Most likely, the applicants will have a BSC and/or PhD
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collaboration and impact. Commitment to safe laboratory practices and structured documentation of synthesis and scale-up procedures. Your Profile Applicants must hold a PhD degree in Chemistry, Chemical
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the department We seek a candidate with the following qualifications : Required: PhD in wildlife ecology, conservation biology, or a related field Experience with technology-assisted wildlife monitoring (e.g
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. Required Qualifications: Completed PhD in the field of Biotechnology, Biochemical Engineering, Biochemistry, or relevant field Strong background in enzymology and protein engineering Experience in enzyme
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you will teach and supervise students at Bachelor’s, Master’s and PhD level and carry out research of the highest international standards in the fields covered by The TrygFonden’s Centre for Child
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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to scientific and non-scientific recipients. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical university globally recognized for the excellence of its
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Professors, three Assistant Professors, a Lab Manager, a Center Administrator, an Administrative Supporter and approximately 15 – 20 PhD students, Postdocs, and visiting Scientists. Several POLIMA researchers
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive