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funded by the National Institutes of Health (NIH) to better understand and reduce the process of tumor metastasis, to elucidate immune responses to ionizing radiation and immunotherapy, and to improve
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, and climate projections depends critically on the adequate representation of land-atmosphere (L-A) feedbacks. These feedbacks are the result of a highly complex network of processes and variables
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or Functional ultrasound imaging or Electrophysiology (neuropixels) in behaving animals Quantitative data analysis and computational modeling of network activity Data acquisition systems, signal processing and
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control Correlation between process conditions, material properties, and ATOX resistance Contribution to the preparation of scientific reports, presentations and publications. Collaboration with academic
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The Fuccillo Lab at the University of Pennsylvania is seeking postdoctoral fellows to join our team and contribute to projects investigating how rodent cortico-basal ganglia circuits control valence
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and actuate [2], which opens new possibilities for controlling cellular function. In the recently funded RIBOTICS (RNA Origami Technology in Cell Systems) project, the lab aims to develop RNA origami
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controlled trials Compensation: The current pay range for this position is $62,232 - $75,564 per year. Position Description: We are seeking a postdoctoral researcher to work in the lab of Dr. James Griffith, a
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Are you interested in Robotics and can you contribute to the development of the project Dynamics and Control of Robotic Handling and Maintenance of Fusion Reactors? Then the Department of Mechanical
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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
) This position centers on directed laboratory evolution of defined microbial communities under controlled bioelectrochemical conditions. You will run evolution experiments with constructed consortia, track
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or functional genomics datasets. Strong programming skills in Python and/or R, with experience in version control (e.g., Git) Familiarity with machine learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow