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tools for High-Performance Computing (HPC) applications. Qualifications/Requirements Qualifications / Discipline: - PhD’s degree in Physics, Materials Science, Computer Science, Data Science, Artificial
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, spatial transcriptomics, and high-plex immunofluorescence spatial proteomics to uncover disease mechanisms. Perform data mining, integration, and visualization, extracting meaningful insights from diverse
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to support teaching activities as required by the school. Key Responsibilities: Develop algorithms and/or data structures, along with appropriate computation models. Perform empirical validation
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experience with coding in R, Matlab and/or Python, and already adapt to using the UNIX command line and executing analyses using high performance computing cluster. Preferred qualifications: Prior experience
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cancer genomics and functional interpretation of genetic variants. Proficiency in Python, R, or other bioinformatics languages. Knowledge of cloud computing, and high-performance computing (HPC
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that directly relate to this position. PET NeuroImaging Data Analysis: Multimodal Data Integration for Neuroscience Applications The successful candidate will work on projects performing analysis of PET
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. Key responsibilities will include: Research: Conduct and publish high-quality research using best-practice methodologies while developing a coherent research program and emerging research profile
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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approaches for resistome prediction or biomarker discovery is a plus. Why Join Us? Access to cutting-edge technologies (mass spectrometry, next-gen sequencing, high-performance computing). Work on high-impact
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program. Publish research in peer-reviewed journals and present work at scientific conferences aligned with business objectives. Demonstrate a high degree of responsibility in maintaining scientific