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Field
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of computational tools for process monitoring and predictive analysis Candidate Criteria Applicants should have: A PhD in Process Engineering, Chemical Engineering, or a closely related field Strong expertise in
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments
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research, digital health solutions, and the development of AI-based predictive models using large-scale clinical datasets. This position is particularly suited to a clinician-scientist with a strong
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Engineering » Mechanical engineering Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 2 Oct 2026 - 00:00 (Europe/Brussels) Country Poland Type of Contract Permanent Job
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(3) Machine Learning (ML) approaches that improve determinism and predictability across IBF and APPF processes. This position supports an integrated program encompassing advanced control for IBF, APPJ
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predict the behavior. You will be embedded in our team, which holds dedicated in-house expertise in 3D printing, pH-feedback systems and modeling, and you will have assistance on the various aspects
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to predict marine extremes for engineering and navigation purposes The PhD candidate is expected to develop an integrated framework that combines machine and deep learning methods with statistical and
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genetic risk scores in independent datasets. Experience evaluating risk scores or prediction models, including assessment of diagnostic or predictive performance in biomedical data. Desirable Criteria
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systems to operate safely and efficiently. Possible research directions include advanced flight control, model predictive control, nonlinear control, fault-tolerant control, cooperative control and aerial
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between pollution control efficiency, electrochemical yield, and energy recovery potential; • Develop coupled electrochemical and hydrodynamic models to predict process behavior; • Participate in