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subdivisions of the squamate body plan. The candidate will work towards developing computational resources that assist in the data management and analysis of genomic data and its integration with phenotypic data
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development support includes opportunities for conference and workshop participation, and mentoring based on an Individual Development Plan generated by the researcher. The work location for this position is in
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the operation of a wide range of surface science methods, with emphasis on HRXPS, LEIS, AES, LEED, TPD, HREELS, Raman scattering, and SEM. Qualified candidates should possess experience for the design
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/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve goals in the next
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efficacy of such efforts. Responsibilities will include activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and
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of whole genomic data already available; and ii) investigating rates of evolution across the genome and their correlation with phenotypic traits across various subdivisions of the squamate body plan
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candidates with strong expertise in building and conducting ultrafast time-resolved optical experiments. Key skills include the ability to design, assemble, and align ultrafast optical setups, integrate setups
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activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers in
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A complete application will require: 1.A current curriculum vitae; 2.A brief cover letter (not to exceed 1,000 words), describing the kind of research that the candidate would plan to pursue in
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the Department of Chemical and Biological Engineering to study the biochemical and mechanical mechanisms that define pattern formation during branching morphogenesis of the lung and mammary gland. Further