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in CFD software tools such as Ansys Fluent and CFX and with experience in coding using MATLAB, Python, and User-Defined Functions (UDFs). Strong technical communication skills. At Level B
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, such as Python and MATLAB (by MathWorks), for data analysis, simulation, and automation tasks. The successful candidate may be required to complete a number of pre-employment checks, including: right
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communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is desirable Knowledge and interest in wine is desirable Applying: Expression of
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principles. The candidates must also be able to quickly grasp emerging trends in the relevant discipline. The candidate should be willing to work using different programming languages/frameworks such as Python
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of the following areas: machine learning, energy system modelling and simulation, or digital twin systems. Proficiency in programming languages (e.g., Python, MATLAB, or similar) and experience with
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visualisation, and programming languages like Python or R, along with understanding of data management and machine learning; exemplary experience and confidence in undertaking all aspects of stakeholder
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programming languages such as Python, R, or JavaScript. Integrate geospatial data with other systems and applications through APIs and SDKs. Maintain and enhance existing geospatial processes and workflows
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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skills in R and Python. Demonstrated experience with the handling and maintenance of crops in field-based and controlled environments, and genetic transformation of cereal crops. A strong track record of
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various sources. Required knowledge Python programming Machine learning background Image analysis Video analysis