A special case of 2 jointly Weak-Sense Stationary (WSS) stochastic processes
Yes, when $R_{X,Y}(t_1, t_2) = E[X(t_1)Y(t_2)] = 0~ \forall ~t_1, t_2$, $\{X(t)\}$ and $\{Y(t)\}$
are often called uncorrelated WSS processes,
and they are considered to be jointly WSS processes.  More nitpicky folks
agree that the processes are indeed jointly WSS when $R_{X,Y}(t_1, t_2) = 0~ \forall ~t_1, t_2$, but insist on reserving the adjective uncorrelated 
for processes for which the cross-covariance function
$$C_{X,Y}(t_1,t_2) = E\left[\left(X(t_1)-E[X(t_1)]\right)\left(Y(t_2)-E[Y(t_2]\right)\right] =E[X(t_1)Y(t_2)]-E[X(t_1)]E[Y(t_2)] = R_{X,Y}(t_1,t_2)-E[X(t_1)]E[Y(t_2)]$$
equals $0$ for all $t_1, t_2$, that is, every pair of random variables $X(t_1)$, $Y(t_2)$ from the processes is a pair of uncorrelated random variables.  Of course, when at least one of the processes has zero mean
(as is usually the case in signal processing applications), then
$C_{X,Y}(t_1,t_2) = R_{X,Y}(t_1,t_2)$ and so the nit gets picked without
requiring any further consideration.