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across a range of clinically relevant pathogens. Develop novel computational methods to infer biological function directly from protein sequences, including modeling epistatic interactions and residue
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, languages and research methods. Shortlisted candidates will be invited to submit a 1,500-word research proposal before the interview and to present their proposed project during the interview. Applications
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statistical / machine learning methods, pathway/network analysis or artificial intelligence approaches. Other requirements: The candidate should have a PhD or equivalent degree in bioinformatics, artificial
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technique, such as PVD, PECVD, ALD, spin-coating, electropolymerization, or any equivalent method. Expertise in electrical and electrochemical characterization techniques is required, ideally including
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, pure N/P-doped SiC, and mixed graphene/SiC-based formulations will be considered for both granulation methods; core (SiC) / shell (graphene) granules may complete the material range applying co
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. - Proficiency in research methods in the humanities and social sciences, particularly semi-structured interviews - Knowledge of press databases - Proficiency in analysing press corpora - A willingness to work in
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-phenotyping of individuals with autism and controls including brain imaging (EEG and MRI) and a battery of cognitive tests. Our group is currently developing new methods for analyzing whole genome and brain
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data analysis in cosmology and astroparticle physics. These positions focus on the development and application of SBI methods in two contexts: spectroscopic galaxy surveys and the gamma-ray sky
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and economic experiments, analyzing data with advanced statistical methods (i.e., econometrics), and drafting research papers. In addition, the post-doctoral position will involve training and managing
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods