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Field
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background in Mathematics/Applied Mathematics, particularly in research areas such as Applied Analysis/Computational Mathematics/Mathematical Modeling/Probability and Statistics, along with excellent
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Appointment Term: 1-3 years Appointment Start Date: As soon as possible (but also interested in candidates who want to start later) Group or Departmental Website: https://profiles.stanford.edu/pascal-geldsetzer
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Annual Basis: 9 Month Review of Applications Begins July 2, 2026; position open until filled Special Instructions to Applicants Apply online at https://www.mathjobs.org/jobs/list/28408 by submitting a
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of the research field Critical Infrastructure Resilience Knowledge of Collaboration theories Ability to conduct social network analysis, statistical analysis of surveys, or modelling of critical infrastructures
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development of digital ICF-based tools * working with data collection, data management, statistical analyses and/or qualitative analyses * writing and publishing scientific articles in international peer
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transport, urban planning, public policy What you will do Develop conceptual frameworks for mobility service usage Statistical analysis of surveys Qualitative interviews with residents in Gothenburg Supervise
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data analysis, such as signal processing, modeling, statistics, or machine learning Excellent written and verbal communication skills in English, particularly in a research context It is meriting to have
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(Computer science, Statistics, Bioinformatics, Physics or similar fields) or in Life sciences with a strong computational and programming background. All But Degree (ABD) status will also be considered
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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statistical analysis. Experience in remote sensing, UAV-based sensing, and plant phenotyping. Experience working with large-scale image datasets and artificial intelligence methods. Personal Qualities We