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in artificial intelligence (AI) to join our growing biomedical innovation team. In this pivotal role, you will lead and contribute to the design, development, and deployment of machine learning
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data types (transcriptomics, proteomics, imaging). AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. FAIR
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data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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(transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional
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methods relying on machine learning, artificial intelligence, or other computational techniques. Duties The position includes research, teaching and administration. Duties includes conducting research
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: Experience combining proteomics with genomic/transcriptomic data Specialized knowledge: Understanding of peptide-spectrum matching, FDR estimation, protein inference AI/ML proficiency: Experience with machine
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on machine learning, artificial intelligence, or other computational techniques. Main responsibilities Research and in addition some teaching and supervision. Qualification requirements In order to qualify
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strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Work duties The
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Lab (learn more at lab.winkler.site) at the Division of Micro- and Nanosystems. Our Lab develops microsystems for life science applications, including as part of the ERC-funded project CHIPzophrenia in