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Field
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required to make data driven discoveries that increase our scientific knowledge and improve the quality of life. We architect ecosystems of large-scale commons of research data, computing resources
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involved in the bioinformatic and analytic aspects of predictive modeling. MINIMUM JOB QUALIFICATIONS: A Ph.D. in bioinformatics, genetics, statistics, mathematical, physical, or computer
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essential components of SPARC's AI-accelerated drug discovery pipeline, direct in silico computational studies, and lead lab-in-the-loop collaborations with UAB, regional, and national experimental partners
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encourage candidates with a strong background and experience in theoretical, algorithmic, or applied research in biomedical informatics. Candidates should demonstrate a strong scholarly record of research
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experience in analyzing genetic, genomic, or image data. Ability to program at a high level in R or Python. Ability to work independently. Experience with analyzing single-cell and spatial omics data. Working
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collaborative, high-impact career development team and as a school liaison for the School of Engineering and Computing, in addition to designated industry career communities, building structural bridges between
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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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extend the core computational infrastructure that underpins a multi-scale immune digital twin ecosystem and platform. Collaborate closely with product leadership to translate near-, mid-, and long-term
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Associate will contribute to a research program focused on driven quantum systems and their applications to quantum information science, particularly in superconducting circuit platforms. This work includes
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designing, executing, and analyzing current or future quantum simulations at the intersection of subatomic physics and quantum information science. The successful candidate will also lead peer-reviewed