26 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" Fellowship positions at University of Texas at Austin
Sort by
Refine Your Search
-
remarkable rate, launching thousands of successful careers and developing Texas Engineers into industry leaders Dr. Passalacqua and Dr. Moodie will supervise the post-doctoral scholar and the scholar can be
-
research described above. Data collection, data curation, data organization and data analysis, bioinformatic analysis, run computational pipelines, survey literature. Properly document lab notebooks
-
of bacteria, isolation of RNA and DNA, PCR, RT-qPCR, reporter assays, protein expression and purification, in vitro mutagenesis, and RNA sequencing and data analysis. Provide instruction, assistance and
-
within the Laboratory of Dr. Zunlong Ke at the Department of Molecular Biosciences, the University of Texas at Austin. This Postdoctoral Fellow position is funded by Cancer Prevention and Research
-
information; at least one reference should be from a supervisor Letter of interest Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your
-
sustained research trajectory in addiction health services research and policy evaluation. Responsibilities Design and execute advanced quantitative analyses using large secondary administrative health data
-
Conduct experiments to evaluate membrane ion–ion separation performance. Maintain accurate experimental records and prepare data for publications and presentations. Work effectively in a collaborative, team
-
experimental expertise in large-scale fluorescence data collection and analyses. Ideal candidates will have additional experience in flow cytometry, imaging, cell culture, next-generation sequencing, and
-
references with their contact information; at least one reference should be from a supervisor Letter of interest Important for applicants who are NOT current university employees or contingent workers: You
-
microscopy systems that integrate machine learning, robotic control, and real-time data analysis to achieve autonomous imaging and interpretation of complex materials systems. The Fellow will design and