PhD in Network Science: Modeling of Animal Networks 80 %, Zürich (Kreis 11)

Responsibilities

Develop and implement temporal multilayer network models combining behavioral, genetic, and social data Develop and implement network null models for statistical tests of inbreeding avoidance Build simulations of mouse population dynamics for benchmarking and power analysis Collaborate closely with biologists and geneticists to ensure the biological validity of computational methodsDisseminate results in high-quality peer-reviewed journals and at international conferences Qualifications

Fascinated by fundamental questions in network science and complex systems, with an interest in evolutionary biology MSc (or equivalent) in applied mathematics, physics, computational biology, or a closely related field Strong programming skills (Python); familiarity with graph libraries is an advantageBackground in network science, graph theory, stochastic processes, or statistical inference Ability to work independently in an interdisciplinary research environment Strong interpersonal and team collaboration skills Fluency in spoken and written English

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