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curious to deliver work that matters, your journey starts here! The Language Technologies Institute (LTI) at CMU is a world-renowned research and education hub at the forefront of natural language
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will possess: A strong background in scientific programing Interest in developing open-source data analysis and modeling tools in one of the following languages: Python, Julia, or C . A strong interest
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learn mathematical modeling and quantitative analysis Ability to program in at least one of the following languages: Python, MATLAB, R or C Evidence of outreach, mentoring or community building. Required
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of the essential functions with or without a reasonable accommodation. ---- Retirement Plan Eligibility: The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position
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are accepted). References. Contact information for references from the PhD programme or previous employment are encouraged. The application and appendices with certified translations into English must be
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. Excellent communication skills in English and the ability to work collaboratively. The ability to direct and take ownership of research projects. Desirable Experience with the zebrafish model Experience with
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
for the formation of model membranes e.g. LB/LS deposition, RSE, etc. We Offer A friendly and respectful English-speaking working environment. Flexible working hours. Access to a world-class laboratory with state
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., DDS etc) in an appropriate field. Excellent scientific writing ability and strong oral communication skills. The ability to work effectively and collegially with colleagues. Additional qualifications as
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engineering methods (e.g., via CRISPR). Plan and execute experiments to probe robustness of tissue morphogenesis, particularly through quantitative imaging and large-scale molecular profiling (e.g., via scRNA