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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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, or cyber-physical systems Strong expertise in at least one: power system dynamics, inverter-based resources, microgrid modeling, or nonlinear control Solid foundation in dynamical systems, optimization
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the recently upgraded hadron calorimeter, trigger system optimization, and improvement of particle flow reconstruction. We are currently engaged in measurements involving the top quark, searches for rare Higgs
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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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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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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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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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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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techniques such as cloning, PCR, mutagenesis, DNA extraction, gel electrophoresis 4. Knowledge of protein/antibody discovery and optimization using in vitro display (such as phage or yeast) technology 5