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to seminars and academic programming at UPenn Opportunities to contribute to research and publications Participation in lab retreats and networking opportunities Exposure to a highly collaborative academic
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, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training procedures affect model behavior
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to research and publications (as applicable) Access to a collaborative academic and scientific network at UPenn What You’ll Do: Lead day-to-day laboratory operations, including equipment oversight and supply
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, custom-trained neural networks, and related tools. Analyze and interpret high-dimensional neural datasets using systems neuroscience approaches such as neural networks, Bayesian inference, and decoding
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in a research environment a plus General languages (preferred): C++, Python, MATLAB CUDA (strongly preferred) Machine learning knowledge. e.g. logistic regression, SVM, neural network models Basic
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use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for microscopy image analysis are especially relevant. Include a link
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career pathways — BBB research is highly applicable to both. Ongoing networking support, including conferences and collaboration opportunities. The opportunity to shape the direction of a growing, high
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genes, regulatory networks, and signal transduction pathways underpinning the patterning and differentiation of stomata, cellular valves that support our life and sustenance. We are now expanding our
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conquering disease. With regular symposia, daily seminars, and several large graduate programs, Harvard Medical School allows trainees to network, realize their career goals, and reach their full potential as
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of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code