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Field
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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, you will be focusing on the topic of Brain Neuro-Adaptability to Pain, in particular brain oscillations in pain conditions and non-invasive brain stimulation. You will be working alongside PhD students
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work. About You (Selection Criteria) Essential (Level A&B) A PhD in a relevant discipline (e.g. nursing, pharmacy, epidemiology, health services research) Peer-reviewed publications. Research experience
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experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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). Experience with known packages for machine learning, such as scikit-learn or others. Experience with deep learning techniques and software packages such as PyTorch or similar. A published example of a
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. The department offers an epidemiology PhD, Master of Science, and concentration in the MPH program. It is also home to two National Institutes of Health Training grants (T32). Faculty members are strongly
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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Postdoctoral Associate - AI3 Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in hand by the start of the appointment. Preferred Qualification: A
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methods, risk and reliability, stochastic control processes, dynamic programing, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong