54 parallel-processing-bioinformatics Fellowship positions at The University of Queensland
Sort by
Refine Your Search
-
via the academic promotions process. Questions? For more information about this opportunity, please contact Professor Leanne Hides . For application inquiries, and to request the full position
-
including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in
-
loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You
-
opportunities via the academic promotions process. About You Completion of a PhD in the area of carbon management in the mining industry A sustained record of outstanding impact and achievement in research in
-
loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Level
-
staff, including hands-on guidance in strain engineering and fermentation processes. Support the professional development of junior scientists, engineers, and technicians by sharing knowledge and best
-
/finish times, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in applied mathematics, mathematics, statistics, operations
-
the Research Fellow will investigate the process of micropinocytosis, the drinking cells, and study mechanics and forces on cellular level during this process. Produce quality research outputs consistent with
-
loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You A PhD
-
collaborating with industry partners on a project aimed at developing kinetic Monte Carlo simulations to model epitaxial growth processes. The goal is to control and optimise the growth of nanoscale structures