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- Zintellect
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Field
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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across time and contexts. Job Description: You will develop and apply mathematical models and machine learning algorithms to analyze the structure and evolution of knowledge systems across different
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members Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous
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performance. 3) Detector systems: Characterization and modeling of HxRG detector readout schemes and analysis protocols. 4) Data analysis: Experience with instrumentation data analysis software and algorithms
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans for patients with chronic diseases. Analyzes complex sensor data, works with a
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lab/field validation. - Strong DSP/algorithms and real-time control; proficiency in Python/Matlab. - Experience integrating optics with electronics and firmware. - Track record of publications in fiber
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of computer science fundamentals including algorithms, data structures, and object-oriented programming. Proficiency in C/C++ or similar language Working with large codebases Containerization (Docker) and building
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. Basic Qualifications: A PhD degree in civil, chemical, or environmental engineering. A minimum of 2 years of experience in the use of Python for programming of data analytical models and algorithms
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Integration: Integrate multi-modal data (e.g., single-cell RNA sequencing, spatial omics) to uncover new insights into cancer biology and therapy. Algorithm Development: Create and refine algorithms
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners