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computation. Prior experience with DNA strand design or molecular computing is desirable. You should be able to plan and execute your own research, engage in scientific discussions, and work as part of a
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Familiarity with optimization algorithms and design of experiments methodologies Experience with high-performance computing environments Track record of publications in peer-reviewed journals Previous
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operate normally. Responsible for the establishment and improvement of equipment management system, including the use of norms, safety operating procedures. 2. Experiment Design and Execution: Design and
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research student in an engineering/virtual lab. With excellent communication skills, the candidate will have expertise in the design and execution of engineering experiments but also in the design and
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of their scholarship. Responsibilities Plan, design, and execute complex research studies, procedures, and protocols. Lead and manage assigned discovery and research projects, coordinating all study activities. Organize
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, sustainable medium for molecular computation and data storage. The successful candidate will lead the design and modelling of thermally regulated DNA motifs and contribute to the development of an automated and
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. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with
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: Design AI models capable of predicting memory access patterns. Integrate these models into the USM platform, conduct experiments, and analyze the results. Write and submit a scientific article presenting
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engineer or computer scientist to establish a robotic platform for autonomous experimentation in organoid culturing. You will work with life scientists to design, integrate, and establish the platform’s
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, particularly head/skull injury mechanics or impact biomechanics Knowledge of material characterization techniques and experimental mechanics Familiarity with optimization algorithms and design of experiments