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Field
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of childhood allergic diseases. The candidate will develop machine learning–based biomarker prediction models to identify microbiome-derived signatures associated with allergy risk and immune tolerance outcomes
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
-driven Earth science. The successful candidate will develop independent and collaborative research that integrates large-scale geodynamic and plate-reconstruction modelling with advanced statistical and
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developing the project’s analytical model. c) Participation in building a database of all TEIP schools belonging to the IE-ULisboa Redescola network. d) Establishing initial contact with the principals
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learning models applied to material modeling. Proficiency in programming languages, such as Python, MATLAB, Julia, and C++, and molecular dynamics programs, such as LAMMPS, to predict mechanical/electrical
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hydrogenation, dehydrogenation, and hydrogen transfer reactions. Detailed characterization and kinetic studies will be performed to test computational predictions and microkinetic models, and to refine machine
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driven predictive models to improve optimisation, consistency and overall yield. The main focus for this role is to work with the driven research team who are at the forefront of sensor technologies
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model cell membranes. • Establish predictive models for peptide-induced transport and cell membrane deformation. • Create a training hub for young scientists to prosper in a multidisciplinary
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Council of Norway, is organised as a section at the Department of Geosciences. PHAB’s main goal is to develop predictive models to identify habitable planets around other stars. Within three different
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other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases
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or the adaptation of existing tools and techniques for spatio-temporal analytics, such as representation, exploratory visualization and theories and mathematical model development of spatio-temporal data. Support