  We examine the innovation of researchers with long-lived careers in Computer
Science and Physics. Despite the epistemological differences between such
disciplines, we consistently find that a researcher's most innovative
publication occurs earlier than expected if innovation were distributed at
random across the sequence of publications in their career, and is accompanied
by a peak year in which researchers publish other work which is more innovative
than average. Through a series of linear models, we show that the innovation
achieved by a researcher during their peak year is higher when it is preceded
by a long period of low productivity. These findings are in stark contrast with
the dynamics of academic impact, which researchers are incentivised to pursue
through high productivity and incremental - less innovative - work by the
currently prevalent paradigms of scientific evaluation.
