During the Covid-19 crisis, many firms shifted work from office and other business locations to the workers' home or other remote locations. After the crisis many firms continued this practice, with job postings that said work was to be done in part or entirely at home. This project developed an algorithm to take the millions of job postings and turn the text of the postings to measure the share of job postings that offered the potential for WFH from the period before the pandemic through the pandemic and afterwards. The project examined the type of work, measured by occupation and work activity, that were open to WFH and the relation of this type of work to the activity of posting firms. The results advanced our knowledge of how firms altered the location of work, of the types of jobs amenable to WFH, and of the variation in firm ability or willingness to shift work from business locations to workers' homes. The data revealed huge differences in postings for WFH among occupations with differing content of work and also showed substantial differences among firms hiring workers in the same type of work. Since job postings on the Internet have become a major source for firms and workers to connect in the job market and provide near real-time information on demand for labor, the analysis adds to the US's knowledge base for reaching better employment outcomes than traditional analyses based on surveys of firms and workers that take longer to process. The algorithm developed will help firms, workers, and government agencies better assess the state of WFH in a dynamic labor market and can be modified to measure other aspects of demand for labor beyond WFH.