This report investigates a scheduling problem where task duration is uncertain. The duration per task has a lower and upper bound, and is dependent on observed duration of other tasks. This tries to closer model real life. We reduce all possible different outcomes to a few extreme scenarios. The report compares two types of heuristcs: one which always chooses the longest duration task first, and one which tries to minimize the uncertainty by choosing tasks that reveal the most information. In the end, we find that the heuristic choosing the longest duration task first competes fairly well with the other type of heuristics.