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defence are eligible for appointment. Demonstrated experience in epidemiological modelling and infectious disease dynamics Experience working in interdisciplinary teams Proven skills in statistical analysis
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interdisciplinary teams Proven skills in statistical analysis and mathematical modelling tools Excellent knowledge of programming languages such as R, Python, etc. Familiarity with AI algorithms and machine learning
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Proven skills in statistical analysis and mathematical modelling tools Excellent knowledge of programming languages such as R, Python, etc. Familiarity with AI algorithms and machine learning Excellent
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statistical analysis of high-throughput sequencing data Candidates without a master’s degree have until 30 June 2024 to complete the final exam. Grade requirements: The norm is as follows: The average grade
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modelling and infectious disease dynamics Experience working in interdisciplinary teams Proven skills in statistical analysis and mathematical modelling tools Excellent knowledge of programming languages
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interdisciplinary teams Proven skills in statistical analysis and mathematical modelling tools Excellent knowledge of programming languages such as R, Python, etc. Familiarity with AI algorithms and machine learning
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experience in epidemiological modelling and infectious disease dynamics Experience working in interdisciplinary teams Proven skills in statistical analysis and mathematical modelling tools Excellent knowledge
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, epigenetic and phenotypic analysis of plant reproduction Documented hands-on experience with bioinformatics and statistical analysis of high-throughput sequencing data Candidates without a master’s degree have
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experience in epidemiological modelling and infectious disease dynamics Experience working with social economic components in epidemic research. Proven skills in statistical analysis and mathematical modelling