We recently put out a position paper titled "Neurosymbolic Programming for Science"
https://arxiv.org/abs/2210.05050

This position is informed by our experience collaborating with scientists: science is an iterative process of analyzing data, proposing hypotheses, and conducting experiments. Because scientists reason more readily in symbolic terms, it is important to develop frameworks that natively inherit the both the flexibility of neural networks and the rich semantics of symbolic models.