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Computer Science or a related field Proven ability to conduct independent research with a relevant publication record Outstanding data analytics, mathematical, and computer modelling skills Excellent interpersonal
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Computer Science or a related field Proven ability to conduct independent research with a relevant publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal
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knowledge in basic soil mechanics is required. Have a degree in civil engineering. Possessing a Master’s or PhD degree will be advantageous Knowledge of physical modelling will be advantageous. Key
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team to develop/produce/investigate extraction and fractionation of mung bean/rice/spent barley for improved functionality, generate process data for future life-cycle assessment and techno-economic
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of measurement results Coordinate very closely with research team and industry partner in the project execution and in the procurement, process including liaison with test and measurement equipment/services
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. Stakeholder Management responsibilities include acting as the primary point of contact for all project stakeholders, and in the process, building and maintaining strong relationships with industry partners
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, capable of engaging both technical and non-technical audiences. Application Process Applicants are required to submit a CV, cover letter, detailed research proposal, and references to the SIT recruitment
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. Operate the simulated electrical model on a real-time system such as Typhoon power-in-loop and Opal-RT systems with physical real connections to the EMS controller to perform deterministic simulations
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the agility of their multi-product manufacturing process in an uncertain environment. To this end, by working closely with subject matter experts from the PIPS member companies (i.e., GSK, MSD, Pfizer, and
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hydrodynamic modelling and sediment transportation. ii. Model Validation: Validation of DHI Mike Model with past historical data iii. Data Analysis: Process and analyze coastal and ocean wave data to improve