This postdoctoral fellowship (postdoc) position is intended to train a recent PhD in the research, teaching and professional development to make her/him competent for a tenure track academic position at a research university. The postdoc will receive training at the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) under the mentorship of Prof. Amit Sheth in the areas of Kno.e.sis' excellence.
PhD in Computer Science or Computer Science & Engineering earned by start date or have completed all requirements with formal award due within 4 months of the start date.
Demonstrated success in high-quality publication in the field of candidate's expertise. Demonstrable knowledge of at least two and preferably three or more subjects of relevance to activities at Kno.e.sis with the emphasis on Machine Learning including Deep Learning and Natural Language Processing (NLP), and Knowledge Graphs.
The candidate should have high interest in being trained for a future academic career and should have experience with experimental research, evaluation, data collection, and analysis with scientific thinking. The candidate should have strong technical writing skills as evidenced by publishing in top venues in the candidate's main research area.
Strong programming and systems experience need, including (a) competency in one key language, preferably Python, (b) deep learning frameworks (TensorFlow, PyTorch, etc.).
Experience in (preferably demonstrated through publications in top NLP or AI conferences): Machine/Deep Learning algorithms, Advanced NLP techniques (specifically on biomedical, clinical, and social media text), Cognitive model based computation, Conversational AI.
Experience and/or interest in applying research to medical and public health domains. Experience of effectively using GPU an/or cloud computing environments.
Essential Functions and percent of time::
100% The primary areas of research may include building computational models inspired from the human computer interaction, computational linguistics, cognitive psychology, semantic extraction from multimodal (text, image, video) data, and analysis of social media data for studying various areas (examples include: personalized digital health, public health and disaster coordination), with focus on interdisciplinary research. The professional development activities may include manuscript reviewing, serving on conference program committees, organizing workshops, giving tutorials, learning grant writing skills, and exposure to mentoring early stage Ph.D. and MS students.
This is a grant funded position with continuation dependent on funding. Special contract terms and conditions of employment apply.
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