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credits* in chemical engineering, mechanical engineering, applied mathematics, or a closely related field. Strong background in computational modeling and numerical methods Experience with multiphase flow
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. The candidate should be willing to learn basic physical and numerical modeling methods. The successful candidate will demonstrate commitment to the timely completion of deliverables and strong potential to work
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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury
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in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according
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the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according to the criteria of evaluation
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technology or system of higher education, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two
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embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments
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focused on using advanced numerical methods to explore low energy dynamics in strongly interacting quantum spin systems. The candidate will develop and implement advanced algorithms to investigate
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language