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to evaluate the spatial and temporal patterns of how those components interact. And the main focus of your position will be to evaluate how different agroecological practices contribute to soil health
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: Preference will also be given to candidates with experience in: (a) population genetics and genetic data analysis of canids; (b) bioinformatics, including programming in Linux, Python, and R; and (c) oral and
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working directly with stakeholders, observing the outcomes of your work first-hand, and collaborating with different disciplines on shared goals, this is the ideal role for you. Our technology stack is
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representations change across different brain states (awake, asleep, engaged) and track representational drift over extended time periods Analyse recorded animal behaviours throughout experimental trials and
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units for (1) design-based estimation of population parameters, such as the mean and standard deviation of some target property or for (2) model-based prediction (i.e., mapping) of environmental
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on the analysis and comparison of the different methodological approaches used in France and Italy, in order to formalize the definition of “best practices”; Jointly integrating project results into the respective
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projects focused on studying the molecular mechanisms of arrhythmias with emphasis on conduction system diseases. To identify these pathways, the postdoctoral fellow will use mouse models for different
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technologies/platforms (e.g., Salesforce, Marketo, HubSpot) Analytical skills and familiarity with tools for data analysis and visualisation (e.g., Tableau, Power BI, R, Python) General interest in Artificial
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. Criteria Essential or desirable Stage(s) assessed at Experience in developing systems using a variety of technologies. Python followed by Java are our current stacks. Essential Application/ interview / task
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collaborate across a range of individuals with different comfort toward computational biology, including oral and written communication skills. Ability to seek out mentorship and assistance as needed, while