He subsequently worked as a post-doctoral researcher at the Goethe University Frankfurt. Daniel Schmand works on efficient solution methods for discrete mathematical optimization problems, as they occur in production, mobility, company management, medicine, and sport, for example. It is often the case that possible uncertainties, such as defective data or uncertain assumptions, are incorporated and treated as such within the optimization process.