34 machine-learning-phd research jobs at University of Minnesota Twin Cities in United States
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collaborating as a member of a research team. Experience with one or more of the following: machine learning, natural language processing, LLMs Create a Job Alert for Similar Jobs About University of Minnesota
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to the immune system 80% 3D fabrication of immune-related tissue 20% reading literature, writing papers, grants Required Qualifications: PhD in biological science or biomedical engineering, or other field with
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. The researcher should have expertise in computational neuroscience (both neural modeling and machine learning expertise preferred), non-human animal behavioral neuroscience (rat, multi-site silicon probe neural
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coupling between these amacrine cells. Required Qualifications: ⢠A Doctorate Degree (PhD, which is completed within the last 3 years) in the field of neuroscience ⢠Previous experience in dual-whole-cell
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employs machine learning methods to integrate high-dimensional multi-omics data, elucidating biological insights into aging and disease pathways. The successful candidate will specialize in statistical
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. The successful candidate will use different computer programs to analyze viral neutralization assays and antibody binding. Analysis of flow cytometry results will be done using FlowJo or Cyflogic programs and
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above. Preferred Qualifications: ⢠Masters degree or PhD in Biological sciences with a specialization in cellular and/or molecular biology of cancer ⢠Experience working in and managing a research
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material for specialized analysis including PCR analysis. Experience processing and analyzing samples. Experience working with laboratory animals is desired, but not required. Basic computer skills are
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. Proficiency in computer programming in R (preferred) or other languages. Demonstrated excellence in written, virtual, and in-person communication. Ability to work effectively with individuals (students
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external funding for research and outreach and mentor students as relevant. Required Qualifications: PhD in soil science, agronomy, horticulture, environmental science or closely related field with a