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teaching at the secondary or postsecondary level or in industrial training programs. Desirable Education and/or Experience • PhD in electrical or computer engineering or a closely related field, from
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strengths of the University of Tübingen in Computer Sciences and Machine Learning. Potential research directions include, but are not limited to, phylogenetic, demographic, ecological and biogeographic
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research responsibility; however interest in research will be viewed favorably. Lecturer applicants should hold a Master’s degree in Computer Science or Computer Engineering. PhD preferred. Applicants with a
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] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/04/01 04:59 AM UnitedKingdomTime (posted 2026/02/19 05:00 AM
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Caribbean populations of African descent. Most mechanistic insights derive from non-representative cohorts, limiting biomarker discovery and therapeutic precision. Recent multi-omic and machine learning
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to structured programming in C++ and Python - knowledge of linux / unix operating system - fluent knowledge of spoken and written English - fundamental knowlegde of machine learning (and statistics) - good level
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related Data Science area such as Biostatistics or Statistical/Machine Learning and have a track record of independent research of international standing. Reporting to the Head of School of Mathematical
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are essential. In addition to applicants furthering the Department's current areas of specialisation, we welcome those with complementary expertise, notably in continuous optimisation and/or machine learning
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) and Artificial Intelligence (AI). The Department envisions to cultivate a comprehensive curriculum that encompasses key research pillars such as Big Data Analytics and Management, Machine Learning and
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Full Time Open Date 03/06/2026 Close Date Open Until Filled Yes Days Per Week Weeks Per Year Position Description Primary Purpose and Essential Functions Teach a minimum of 20 units (typically 5 courses