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computational science, and Fortran itself is a language that is still in active development (last version is from 2023). However, optimizing and parallelizing Fortran codebases remains a challenge, especially
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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highly automated workflow. This means rather than having a researcher building one strain at a time manually, the same researcher could build hundreds or thousands of strains in parallel using our robotic
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sampling of the parameter space of eclipsing binary observables, most notably photometric data from NASA’s Kepler and TESS missions. In parallel, the applicant will be given an opportunity to teach
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. The next key step is identifying sensors for many new metabolite and drug targets. Our goal is to use a range of novel in-house experimental methods to discover hundreds of new sensors and in parallel
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preferably) Strong skills in turbulence modelling, CFD mesh generation and use of parallel computing Have relevant experience in working with aerosols and droplets Proficient in handling large data sets and
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for Biomedical Imaging (Harvard/MIT/Mass General). In parallel, there will be opportunities to analyze and publish existing data upon identifying areas of mutual interest. The appointment is for one year with a
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packages relevant to biostatistics and bioinformatics (e.g. R, Python, Fortran, Matlab, SAS, Stata or equivalent) and experience in the use of high-performance computer resources and parallel computation
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of structure-function quantifications. We also perform CRISPRa high throughput screening and massively parallel reporter assays (MPRAs) in iPSC-CMs. A current major focus of the lab is implementation of MPRAs
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials