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, innovation, and translational potential. The successful candidate will work on integrative projects involving in vivo mouse models, tumor immunobiology, and multi-omic profiling, with particular attention
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, recombinant protein and isolation and purification, transfection, and aptamer isolation, conduct multi-omics (scRNA/ATAC/scDNA-seq) projects. Assist in the preparation of data and figures for manuscripts and
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intelligence, including reinforcement learning, computer vision, and deep neural networks applied to robotics. Track record of peer-reviewed publications and active participation in interdisciplinary research
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. Demonstrated publication record in statistical methodology and applied biomedical research, with evidence of independent scientific writing. Experience analyzing multi‑omics datasets (e.g., genomics
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thinking skills. Competence in data analysis and visualization using software such as GraphPad Prism, R, or Python. Excellent scientific writing and communication skills, with a track record of peer-reviewed
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genomic changes. In this role, the successful applicant will have the opportunity to participate in the analysis and interpretation of multi-omics datasets including whole genome sequencing, bulk and single
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platforms, as well as extensive networking opportunities within the University of Miami’s robust AI and digital health ecosystem. Program Objectives: Provide fundamental training by interdisciplinary faculty
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collaborative, respectful, and welcoming lab environment 4. Keep track of data, protocols and overall progress in updated laboratory notebooks and data folders’ 5. Communicate and meet frequently with
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rolling basis. Application Requirements: (to be submitted only if requested by the University of Miami hiring team) 1. Statement of career objectives/research goals. The statement should be a maximum of 3
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, with the ability to work independently and collaboratively in a multidisciplinary environment. Excellent communication skills, both written and oral, with a proven track record of publications in peer