118 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Stanford University
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(PhD, MD, or equivalent) conferred by the start date. Proven research and/or professional experience in machine learning and/or natural language processing, with a preference for prior experience working
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. Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred
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learn and master various computer programs. Strong record of peer-reviewed publications. A PhD, MD or equivalent with prior relevant training in Immunology, Biology, Physiology, Biochemistry or related
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decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow collaborative research and mentorship
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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principals to problem solve work. ● Ability to maintain detailed records of experiments and outcomes. ● Ability to quickly learn and master computer programs, databases, and scientific applications
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collaborative culture. The Division of Pain Medicine is at the forefront of innovation in pain research, education, and patient care. Our postdoctoral program has successfully transitioned fellows
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sequence programming (ex: Pulseq) Python, MatLab, C++, etc PyTorch, TensorFlow ML Ops Required Qualifications: MD, PhD, or equivalent Technical interest & expertise in MRI Required Application Materials: CV
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our team. We are looking for postdoc candidates to develop and apply cutting-edge technologies in spatial transcriptomics, single-cell sequencing, machine learning, and functional genomics
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or Chemical Engineering. • Prior work experience in hands-on laboratory experimentation. Prior work in microfabrication, engineering design (computer-aided design), and soft lithography. • Potential experience