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Research Associate, Translational Research Fellow - Dept. Ophthalmology Visual & Anatomical Sciences
and application, CRISPR/Cas mutagenesis, and single-cell RNA sequencing is highly preferred. Proficiency with relevant data analysis and visualization tools (e.g., R, MATLAB, or Python) is required
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. Additional Qualifications: • Theory: Expertise in quantum optics, quantum information science, or quantum field theory. • Simulation: Proficiency in MATLAB or Python for simulation/modeling and data analysis
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characterization (SEM, TEM, XPS, FTIR, etc.) Programming skills (Python, MATLAB, or similar) Exposure to machine learning methods (e.g., Bayesian optimization, active learning) is an advantage Understanding
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understanding of human genetics. Knowledge of DNA and RNA sequencing analysis, of programming languages such as R, Python, or Bash script, and of bioinformatics pipelines for genomic data analysis is essential
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, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
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, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related engineering projects will be an advantage. Key Competencies Ability to build and
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Python or other equivalent programming languages. Strong foundation in data analytics and data-driven modelling. Able to build and maintain strong working relationships with people within and external
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University and the broader NYC cognitive science community. Responsibilities Include: Research & Analysis Develop and maintain Python-based pipelines for large-scale data processing (images/video, text
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, in collaboration with the team responsible for the development of the ApneaScreener algorithm. Knowledge of data analysis tools, particularly Python and R, will be valued to support the interpretation
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models, and foundation models Strong programming skills in Python and deep learning frameworks such as PyTorch Experience with large-scale experiments, model optimization, and performance analysis