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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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29 Aug 2025 Job Information Organisation/Company REQUIMTE - Rede de Quimica e Tecnologia Research Field Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Portugal
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of Research Experience1 - 4 Additional Information Eligibility criteria Candidates must have a PhD in polymer chemistry and physical chemistry in the broadest sense, excellent practical skills, and a keen
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biology and targeted therapeutics Likelihood of advanced skills directly related to the research projects High level of analytical and problem-solving capability Ability to communicate complex information
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experience should cover basic chemistry analytical skills to large scale pilot experience, hands-on, and data analysis. This includes experience on corrosion, kinetics, emission impurities, and solvent
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recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical systems theory Excellent analytical and problem-solving skills Desirable criteria Advanced programming and data analysis
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Science, Operations Research, or Economics Analytical problem-solvers with excellent logical reasoning and a passion for turning data into decisions Clear communicators in a fast-paced and highly collaborative
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing
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Relevant PhD . Or, relevant Master's Degree and 3 or more years of experience . Or, relevant Bachelor's Degree and 5 or more years of experience . Demonstrates broad understanding and wide application
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees