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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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Image processing Optical bench instrumentation – set up and alignment Numerical modelling Scientific software development Geochronology You should possess strong communication and academic writing skills
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the benefits of semantic integration, e.g. in scheduling, resource sharing, or formulation optimization Collaborating with chemical engineers, software developers, and data scientists to ensure practical
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to engage in interdisciplinary collaboration and teaching. Good programming capabilities in advanced analysis software (e.g., Python, R, MATLAB, Julia, or similar) and mathematical optimization suites
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process. Together, these innovations aim to make column generation more practical for solving real-world, large-scale optimization problems. These innovations will be tested within a structured software
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engineering and wave-wind theories is advantageous Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable Ability to work independently
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Energy simulation software, such as TRNSYS, Modelica, EnergyPro Programming languages, such as Python Ability to communicate results in technical reports, and prepare scientific papers for publication in
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or experience in strong collaborations and interdisciplinary work at the intersection between machine learning, geophysics and acoustic data modeling. A strong experience with software defined radio Automatic
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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of AI/ML will be an added advantage. Proficiency with optimization tools and software like GAMS, CPLEX Proficiency with programming languages preferably Python, Matlab Fluency in communication and