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learning models for describing and predicting experimental outcomes. Prior experience in laboratory automation for life sciences is highly desirable. Prior experience with cell and tissue culture is
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of graduate students, undergraduate trainees, and technical staff. The Song Lab employs mouse models, cell culture systems, and molecular and behavioural approaches to investigate brain function and pathology
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Demonstrated experience in developing novel machine learning algorithms and models, supported by peer-reviewed publications or equivalent research contributions. Significant experience applying statistical
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models to address a fundamental question in chromatin biology: How do epigenetic features contribute to the regulation of the genome? We study how chromatin drives specificity for regulating gene
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and modeling of psychopathology and efforts to address behavioral health disparities. This is an excellent opportunity for individuals interested in gaining hands-on research experience in clinical
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REQUIREMENTS We are looking for a graduate student with background in petroleum and natural gas engineering to work on development of advanced AI based models for drilling optimization and wellbore stability
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manner, collaborates effectively, abides by policy, contributes to a positive and productive work and learning environment, and models these behaviours across the institution. Builds and leads diverse
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No. 1 scholarship grant for technological training activities at INFN Structure of Torino for the following research topic: “Device modelling and design of a cryogenic CMOS 28nm Process Design Kit” Where
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Responsibilities 1. performs in vitro experiments on cell cultures, produces, analyzes and processes the results obtained; 2. ensures the implementation of in vitro experimental models and techniques specific
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position involves assisting in the development, deployment, and evaluation of AI-based models and tools for engineering applications. At the end of the project, whole work repository needs to be uploaded in