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on machine learning assisted PSPR optimization of recently developed lean Mg-0.1Ca alloy produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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elements distribution, crystallographic texture), mechanical properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning assisted
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localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy produced by PBF-LB. After identification of the most relevant parameters adopting a
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with e-CALLISTO instruments or Software-Defined Radios (SDRs). · Familiarity with machine learning for astrophysical data analysis. · Knowledge of solar radio data pipelines and event classification
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requirements: - The candidate must be enrolled in a doctoral program in the areas of Computer Engineering, Computer Science, Electronic Engineering, and Computers, or related areas, or in a non-degree program
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season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits An open and collaborative research environment Access to and training in cutting-edge
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sequencing will be highly valued. Interest in applied genetic engineering and synthetic biology. Curiosity and motivation to learn new techniques and protocols. Good time management and communication skills
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25 Aug 2025 Job Information Organisation/Company Consejo Superior de Investigaciones Cientificas Department Centre for Automation and Robotics (CAR) Research Field Ethics in health sciences » Other
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. Please visit the Life in Finland section on our website to learn more. Please note that you must include the following appendices in your application CV (Template for CV, TENK web page ) a list of