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Field
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one or more of the following areas: Programming, Algorithms and computational complexity, Programming languages and compilers, Computer graphics, and Parallel and GPU computing. A typical teaching
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to play an integral role in exciting collaborations, both within St. Jude and with prominent external collaborators. A deep understanding of cancer genomics, human genetics, transcriptomics, or epigenetics
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governance, digital campaigning, civic engagement, algorithmic publics, public advocacy, political rhetoric, public opinion, and the ethical, social, and democratic implications of emerging communication
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of the call Past experience in AI algorithms Past experience in Research Projects EVALUATION CRITERIA The selection will be based on the following criteria: Academic record (50%) Past Experience in AI
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languages like Python or C, and or developing and/or using computational methods for analyzing large datasets. Demonstrated experience in developing computational algorithms for solving problems, preferably
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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patients from public repositories (including dbGaP). Develop and apply machine learning algorithms to associate patterns in the data with cancer progression and therapeutic response in prostate cancer
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combination of education and experience. Proficiency in using Python, AI APIs (OpenAI, Anthropic, Gemini, etc.), machine learning algorithms, and software development frameworks. Familiarity with building
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chromatography/mass spectrometry (LC-MS) measurements using principal component analysis, partial least squares, genetic algorithms, and other multivariate statistics. Current projects have accumulated a
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; develop and validate an astrodynamics-based orbit determination algorithm using TFC, including hybrid solutions with stochastic filters (eg, EKF or UKF); integrate and calibrate optical sensors and develop