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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b) Computer Science/Mathematics/Physics and at
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) Computer Science/ Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Additional
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for mathematics research and education. The Computational Biology and Biostatistics groups develop mathematical models to address biological phenomena like systems biology, cancer modeling, statistical genetics
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of Computing Science , Mathematics and Mathematical Statistics , Molecular Biology , Plant Physiology and Clinical Microbiology . More information regarding accessible research infrastructure can be found here
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) Computer Science/Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Selection
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, probability theory, etc) A competence in quantitative topics equivalent to a mathematics, statistics, physics, computer science, or engineering degree is required (if your degree was not in one of these domains
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are required: You have graduated at Master’s level in bioinformatics, computational biology, data analysis, computer science, biostatistics, biological engineering, applied mathematics/physics or completed
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high