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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
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2025.The position is part of the project "Validating fatty acid synthesis enzymes as targets for antibiotics against Pseudomonas aeruginosa and other Gram-negative bacteria”, financed by the Research
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postdoctoral research fellow position within medicinal chemistry. The position is for a fixed term of three years and is associated with the project "Validating fatty acid synthesis enzymes as targets
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"Validating fatty acid synthesis enzymes as targets for antibiotics against Pseudomonas aeruginosa and other Gram-negative bacteria", funded through the FRIPRO programme from the Research Council of Norway
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communication skills. Fluent verbal and written English language skills are a prerequisite. The following skills would be advantageous: Expertise in the development of methodological approaches for targeted and
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an extensive paleo-proxy archive, in addition to designing and performing targeted modelling experiments. As a PhD candidate at the Geophysical Institute at the University of Bergen, you will also be
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for AI-generated or -scored compounds is presented. If such data is included, it is typically limited to protein kinases which are considered to be easy targets due to wealth of published data. The lack
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insufficiency and cortisol dysregulation. The project targets patients with stress-related hormone conditions, including cortisol deficiency disorders (e.g., Addison’s disease) and cortisol overproduction