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Engineering, Machine Learning, or related fields. Expertise in laser-based metal additive manufacturing process Expertise in data-driven and AI/machine learning research Proficiency in basics of programming
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and generative models for protein structure and function, advancing AI-enabled design-build-test-learn workflows, and creating new tools for the characterization and validation of engineered proteins
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Assistant/Associate Professor of Practice in Human-AI Interaction, Machine Learning, and Data Design
The Iovine and Young Academy (https://iovine-young.usc.edu (opens in new window) ), a nationally leading school for transdisciplinary design and product innovation, is seeking a highly skilled
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materials and structures. By combining numerical modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural
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to develop the knowledge, skills, and attitudes identified in program outcomes. Digital literacy and demonstrated fluency in technology systems, and an ability to model and facilitate use of current
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: Target Discovery → Mechanistic Validation → Molecular Recognition → Therapeutic Engineering → Biotherapeutics Manufacturing Science & CMC → Clinical Translation IMPRINT will leverage advanced modeling
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for research use and eventual integration into offshore engineering design tools. Purpose of the Job The successful candidate will develop and run analytical and computational models of nonlinear waves, floating
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design of formulations and drug delivery systems for small molecules, biologics, nucleic acids, and advanced therapeutics. Biopharmaceutical performance: Mechanistic and data-driven modeling of drug
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retention goals. Supports institutional planning through data driven occupancy modeling and demand analysis. Oversees administrative operations, business services, HR administration, procurement, contract
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About us The Laboratory of Causal Systems Immunology combines large-scale in vivo perturbation experiments, advanced mouse models of immune diseases and causal learning to uncover how genes shape