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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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ecology, environmental science, or a related field, with proven experience in spatiotemporal and multivariate statistical modeling. Particular emphasis will be placed on scientific qualifications relevant
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of relevance: Documented expertise and skills in mathematical modelling of community dynamics is a requirement, and proficiency in statistical time series analyses in community ecology is desirable. Skills in
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samples, laboratory cell lines and animal models. Ongoing and future projects include (i) genomic and functional characterization of molecular drivers of women’s cancers, (ii) biology and therapy
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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modeling of mosquito-borne diseases as proven by peer reviewed publications. Demonstrably strong programming skills in R or Python. Experience with population biology, population genetics, or ecological and
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% women; three continents represented). The strengh relies in coupling: Single-cell microfluidics Quantitative (image) analysis Mathematical modelling Microbiology Molecular biology We approach science with
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wastewater to tackle the environmental threat of AMR. You will have a PhD (or close to completion) in modelling complex systems or a closely allied discipline along with experience in creating, writing
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to illness, parental leave, clinical service, trade union duties or similar circumstances. The PhD degree should be in a computational or life science field, such as bioinformatics, ecology, mathematics
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 3 months ago
: · PhD in Mathematical Biology, Ecological Modeling, Economics, Fisheries Science, or a related field. · Strong background in ecological and/or economic modeling, population dynamics, and quantitative