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extraction techniques. Strong knowledge of protein science and its application in food systems. Proficiency in analytical techniques relevant to food and protein characterization. Skills in statistical
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risk. These studentships are ideal for candidates with a strong background in computational biology, bioinformatics, population genetics, and statistical genetics and an exceptional interest in
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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statistics/ mathematic background Strong programming skills in at least one major programming language Interest in applying relevant mathematical modeling techniques A collaborative team player with a desire
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candidate willing to learn new skills and undertake statistical analyses using a variety of datasets. People within Australia with a relevant Honours or Masters (e.g Public Health, Biostatistics, Epidemiology
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the interface between different scientific disciplines including ecology, evolutionary biology, mathematics and statistics, informatics, economics and social sciences. We aim to apply advanced statistical and
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Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical experiments. Interest in connecting theory
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recruiting participants, to conducting ego-centric network studies and experiments at Dutch schools and Dutch companies); You will use advanced statistical methods to process and analyze data (e.g., social
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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, Soft Condensed Matter Physics , Soft Condensed Matter Theory , Soft Matter , Space Technology and its Applications , spin-orbit coupling , Statistical Mechanics , Statistical physics , Stellar