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machine learning tools on the experimental and numerical data. Requirements Master degree in physics, chemistry, mathematics or related fields Knowledge in materials science Knowledge of python good
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, or modelling. Familiarity with computational tools (Matlab, Python, or finite element analysis). Analytical thinking and enthusiasm for interdisciplinary research. Ability to work independently and as part of a
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competencies/skills required for the project: signal/array processing, machine learning/AI, MIMO/Radar systems, MATLAB/Python programming. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4 Years
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. Hands-on experience in fermentation, microbial cultivation, and analytical techniques (HPLC/GC). Familiarity with bioprocess modelling and simulation tools (e.g., Aspen Plus, MATLAB, or Python), TEA, and
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transport modelling, and data science. Solid programming skills (ideally Python) and experience with data analysis. Self-motivation and curiosity to learn and grow independently. Strong communication skills
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· A PhD in an engineering discipline is mandatory. Experience and skills · Proven programming expertise in Python is necessary; knowledge of other programming languages are additional assets
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ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks is a plus but curiosity, creativity, and enthusiasm are equally important. You will join a
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requirements: Excellent analytical skills Strong verbal and written communication skills Desirable: Strong proficiency in optimising and modelling power and energy systems Programming skills in Python and Julia
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, or energy storage technologies Proficiency in programming languages such as Python, MATLAB, or similar tools A research-oriented attitude Ability to work in an interdisciplinary team and interested in
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, forestry, bioinformatics, or a related field - Strong demonstrated interest in biodiversity, molecular methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work