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Albert Einstein College of Medicine (Bronx, NY) | New York City, New York | United States | 2 months ago
who are interested in applying their expertise to small-molecule drug discovery and translational biomedical research. The project will involve the development and optimization of cell-based and
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numerical techniques to study collective states in active matter. Depending on the candidate's profile and interests, the research can involve various aspects of the modeling and the optimal control of active
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properties of the implanted device using additive manufacturing, to target the patient’s specific condition and obtain an optimal long term outcome. FEM coupled with Design of Experiment (DoE) will guide
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well as to investigate protein–ligand interaction properties; performing protein crystallization and crystal optimization using the robotic facility available in the Structural Biology Laboratory; providing samples and
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analysis, with the long-term goal of enabling health-aware battery management and optimized charging strategies. Qualifications Requirements A doctoral degree or an equivalent foreign degree in Control
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
optimization. Participate in collaborative research projects and mentoring. Contribute to academic publications, reports and seminars The selected candidate will be part of the Foundations Cluster of CIDSAI and
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization
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for acoustic metamaterials/metasurfaces; use simulation and data-driven optimization; contribute to listening tests and VR-based soundscape evaluation; build or test prototypes; publish results; and contribute
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-throughput data, identify differentially expressed genes, explore protein interaction networks, and perform pathway and functional enrichment analyses. Responsibilities also include developing and optimizing