Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs, which specialize for a restricted set of floating point operations only. Many scientific applications, particularly those that are physics-driven and mission-critical, still struggle to adapt to this new hardware trend. To help bridge the gap, the Argonne Leadership Computing Facility (ALCF) invites applications for a postdoctoral appointment on the subject of mixed/reduced precision computing on modern hardware. Duration of the appointment is one year initially and renewable for up to three years contingent on performance and funding. The successful candidate will be supported by ALCF's Performance Engineering group and is encouraged to engage with the broader Argonne scientific community. Moreover, the successful candidate is encouraged to experiment on the wide variety of systems available at ACLF, including both the large-scale production machines and the testbed machines featuring novel architectures such as Cerebras and SambaNova. The list below provides examples of the potential tasks for the successful candidate and illustrates the general nature of the work but is not intended to be exhaustive. In addition, the successful candidate is encouraged to bring their inputs in the research direction during the appointment.