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Field
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strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners on design optimization, life-cycle analysis, and business case
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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for this position, the following is required: PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science, climate etc. with a thesis subject relevant to the description
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Village to calibrate and validate models. Investigating control strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners
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, machine learning, Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, Knowledge of cognitive system is a plus, knowledge of neuronal basis
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conditions. The in vivo work involves close clinal monitoration of compromised neonatal piglet, and their responsiveness toward a set of interventions. The program also involves a series of laboratory
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computer applications used for data recording, analysis, and reporting. Physical Demands and Working Conditions Physical Activities Working Conditions Additional Information Remote Work: A hybrid remote work
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the formula 0,40PQ + 0,40PV + 0,20AI. PQ corresponds to the quantitative evaluation of publications in ISI/SCOPUS journals: in advanced statistical models (e.g., Machine Learning), as well as in programming
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) Country Finland Application Deadline 15 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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, establishment of a seagrass farm, and monitoring of a large living shoreline project. In addition to research, the post-doctoral scholar will be required to teach a 4-5 week-long field course each spring semester