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                ) that encodes transient cellular events into DNA and reads them out by sequencing. Computational challenges include detection of biological signals while applying Record-seq to complex in vivo environments 
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                and outbound prospects related to any outreach and sales activities for SNAI. Devise and implement sales formats enabling multiple prospects to engage with SNAI offerings in parallel (thematic events 
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                their correct anatomical alignment, but conventional implants often require removal once healing is complete, which can lead to complications. Mg-based biodegradable systems could overcome this limitation by 
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                are designed to stabilize fractured bones in their correct anatomical alignment, but conventional implants often require removal once healing is complete, which can lead to complications. Mg-based biodegradable 
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                transient cellular events into DNA and reads them out by sequencing. Computational challenges include detection of biological signals while applying Record-seq to complex in vivo environments (Schmidt 
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                combination of approaches, including high-throughput sequencing and bioinformatics, isolation, cultivation, and physiological characterization of gas-utilizing bacteria, community-level activity and function 
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                between scientific return, technology readiness, and mission feasibility while coordinating with the project manager to align schedule and cost. Lead system-level architecture, design trades, and interface 
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                between scientific return, technology readiness, and mission feasibility while coordinating with the project manager to align schedule and cost. Lead system-level architecture, design trades, and interface 
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                characteristics that align well with the position: You are expected to have a Ph.D. degree in Engineering, Computer Science, Applied Mathematics, or related fields with an excellent track record in competitive 
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                and interpretation of large-scale datasets, in particular next generation sequencing (NGS) data. The team covers raw data processing, high-performance computing, statistical evaluation, interpretation