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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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highly recognized research. More information about us, please visit: The Department of Biochemistry and Biophysics . Project description The successful candidate will develop machine learning (ML
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the country, substantially equivalent knowledge strong programming skills, esp. deep learning prior education and research experience in machine learning In addition to the above, there is also a mandatory
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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data analysis, programming, and biology. You will be part of a collaborative research team with deep experimental and analytical expertise, with access to advanced tumor models and state-of-the-art
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. The long-term goal is to enable targeted interventions for the right individuals, based on their lifestyle, disease trajectories, and molecular profiles. To achieve this, we will apply deep learning models
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for the study of human bone and marrow, and, more specifically, with focus on the analysis of microscopy data with Deep Learning. Doctoral studies comprises four years of full-time study, and leads to a doctoral