Scientific discovery is increasingly enabled by heterogeneous hardware that includes multiple processor types, deep memory hierarchies, and heterogeneous memories. To effectively utilize this hardware, computational scientists must compose their applications using a combination of programming models, middleware, and runtime systems. Since these systems are often designed in isolation from each other, their concurrent execution results in resource contention and interference, which limits application performance and scalability. Consequently, real-world applications face numerous challenges on heterogeneous machines. This poster presents the thread interface of Quo Vadis, a runtime system that helps hybrid applications make efficient use ofheterogeneous hardware, eases programmability in the presence of multiple programming abstractions, and enables portability across systems. Applications using OpenMP or POSIX threads can now benefit from Quo Vadis' high-level abstractions to map and remap full physicspackages to the machine dynamically with a handful of functions. Furthermore, the thread interface has similar semantics to the process interface, allowing scientists to leverage a single-semantics model for partitioning and assignment of resources to workers, whether they are processes or threads. With both process and thread interfaces, Quo Vadis broadens its applicability to improve the productivity of computational scientists across programming abstractions and heterogeneous hardware.