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to global conservation science. To be successful you will need: A PhD in quantitative ecology, quantitative conservation biology, applied mathematics or a related Discipline Publication record in the relevant
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research documentation, including ethics and funding applications Assist with routine team administration Assist with preparing reports, graphs, figures and presentations on research outcomes at different
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we’re looking for: A PhD in Physics, Applied Mathematics, Engineering, Earth Science or another relevant field. Experience in numerical modelling, ideally ice sheet modelling demonstrated through a record
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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging
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farmers, agronomists, and industry stakeholders to understand decision-making processes and simplify data capture and integration workflows. A strong background in data science and decision theory, combined
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or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging project governance, systems thinking, and intelligent control
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
collaborative and forward-thinking research team working across decision and control theory. Responsibilities will include contributing to student mentorship at undergraduate and master's levels and co
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a collaborative and forward-thinking research team working across decision and control theory
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with international colleagues. About the Mathematical Science Institute (MSI) The Mathematical Sciences Institute (MSI) at the Australian National University (ANU) is a leading international mathematics
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how control parameters (e.g. bucket speed, size, depth, and packing density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data