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addressed to the Chairperson of the Jury, submitted through the electronic platform https://apply.fcsh.unl.pt . VIII – If the PhD degree of the winner candidate has been obtained from a foreign university
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postdoctoral position is available in the laboratory of Prof. Alex Persat (EPFL School of Life Sciences, https://www.p-lab.science/ ) to establish a new image-based drug screening platform targeting gram
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international network between PhD students, postdocs, researchers, and industry. Starting date Starting date during Fall 2026. Salary and employment benefits The salary of PhD students is determined according
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environments, and distributional shifts. The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex
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needed for wet-bulb temperature retrieval -Co-locating satellite data with ground-based HadISD stations -Running neural networks and finding the architecture best suited to a case study on India
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. QUALIFICATIONS • PhD in Biological Sciences, Chemical Engineering, or related fields • Strong background in microbiology and quantitative analysis SKILLS • Microbial cultivation and bioreactor operation • Ability
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no less than 5.5 in any band or equivalent). How to Apply Applicants should upload information via Birmingham’s Mechanical Engineering PhD portal here: https://www.birmingham.ac.uk/study/postgraduate
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) Positions PhD Positions Application Deadline 14 Oct 2026 - 11:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer
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monitoring of biomolecules. In this PhD project, you will explore a novel direction: you will study how nanoswitch sensors can be designed for the continuous monitoring of complex nucleic-acids with dynamic