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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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antibody-drug conjugates (ADCs), molecular imaging agents, and targeted therapeutics to improve cancer diagnosis and treatment. We combine protein engineering, chemical biology, molecular imaging
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based surrogate model discovery are strongly
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(i) strong foundations in digital communications and statistical signal processing with (ii) hands-on implementation using reinforcement learning (including multi-agent RL), large language models (LLMs
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: Self-Exciting Point-Process Models of Continuous Home-Cage Behavior Across Genetically Diverse Mice. The project encompasses building behavior based indices of opioid withdrawal with the goal
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Position Description Postdoctoral Associate – National Tutoring Observatory Cornell University Description The National Tutoring Observatory (NTO) is based in Cornell’s Ann S. Bowers College
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formulations to improve pharmacokinetic, pharmacodynamic, and therapeutic properties of investigational agents. Design and perform experiments evaluating formulation performance in cellular and animal models
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(1-2) Applicants with expertise in one or more of the following areas are encouraged to apply: * Foundation Models * Agentic AI * Reinforcement Learning * Medical Image Analysis Position 2: Intelligent
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
-powered research agents for bioinformatics and bioengineering (Bock Lab , CeMM/MedUni Vienna) Building on our CellWhisperer method for chat-based exploration of single-cell data (Schaefer 2025 Nature