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Field
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guidance and mentoring to junior researchers Collaborate with project partners and contribute to publications and software outputs Required qualifications PhD in Cybersecurity, Computer Science, Machine
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; •Strong skills in applied econometrics and individual-level data analysis; •Proficiency in a statistical software package (Stata, R or equivalent); •Research interest in migration, citizenship, and
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experience working with FPGA-based networking platforms/frameworks such as NetFPGA, Corundum, Xilinx OpenNIC, or the ETHZ HLS TCP/IP Stack. Familiarity with Software Defined Networking, SmartNICs, RDMA is an
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software programs including Microsoft Office (Word, Excel, PowerPoint) · Knowledge of computer programming/scripting (e.g., Matlab, Bash/Unix) · Knowledge and experience using image/EEG
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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learning; software development Preferred Qualifications: Excellent academic writing ability on quantitative topics Familiarity with relevant software environments (e.g., R, Python, SPSS) Expertise in
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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software (e.g., MPlus, R, or Stata). Applicants must have graduate training in psychology, neuroscience, medicine, or another advanced degree in a related discipline (Ph.D., Psy.D., M.D., or equivalent); and
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epidemiology and prevention. Proficiency in statistical analysis software such as Stata, R, or SAS. Strong interpersonal and communication skills, with the ability to collaborate effectively in a team
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software in support of Department of Energy (DOE) mission applications across a broad range of scientific domains, including materials, biology, physics, and nuclear science. The successful candidate will