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machine learning framework that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenomic features, and three-dimensional (3D) genome organization—to identify
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to disease prediction and prevention. Through our Team Science approach, we have achieved breakthrough discoveries in five key areas: neuromodulation (reinforcement learning), critical period mechanisms
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related research field is advantageous. Experience with instrumental texture, image analysis and particle sizing techniques (e.g., texture analyzers, universal testing machines) is highly desirable. Strong
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nucleic acid-based targeting agents to treat prostate cancer. The successful candidate will focus on the design, synthesis, modification and biophysical characterization of DNA aptamers. This position would
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research, supervise
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post-metamorphic cell types. Finally, live imaging and transgenic approaches will be employed to trace the developmental origins and lineage relationships of these cell populations. Where to apply E-mail
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imaging techniques and flow cytometry to address key questions. The prospective candidate should have the knowledge to perform cell culture works and a willingness to learn and trouble shoot new techniques
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-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . Our lab studies spatial population genetics, using simulation-based inference and machine learning to infer
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and inclusive workplace. To learn more about our culture and hiring process, visit our Jobs at Macquarie page.