[re]searching curates its own databases, which means that all of the databases users have access to are generated by the users themselves. This ensures that we present users with only the most relevant information, and that the databases evolve to consider any new or emerging technologies.
This page presents an (anonymised) glimpse into some of the data that [re]searching is collecting, and how we think it can be helpful to universities and research institutes, as well as companies.
As well as enabling fruitful mentor-mentee relationships and helping our users find exciting new careers, we are also interested in using a data-driven approach to allow universities and research institutes to design programmes to tackle this problem at its source. If our data can be used to improve the training PhD students receive to pursue a diverse range of careers, then we will be tackling the problem of over-supply of PhDs from two different angles. We can use this data to, for example, map skills to job titles, or industries, to provide a highly detailed information to help mentees prepare for specific careers.
If you are interested in obtaining access to this data for academic training purposes, please get in touch with us.
Similarly, companies can benefit from this data to perform highly targeted recruitment, as well as gaining insight into the skills associated with different academic disciplines.
Companies are now invited to register for an account to show their interest.
[re]searching is a globally distributed network. We firmly believe that a mentee based in New York has just has much to learn from a mentor in Paris or Pamplona as they do from someone in the same city.
We have more mentees than mentors in our network, but since launching we have maintained a mentor:mentee ratio of around 1:9.
This is expected, as there will always be more PhD students and postdocs looking for jobs than available mentors, but we feel that this ratio strikes a good balance between providing information for mentees and not overwhelming mentors.
Our users come from a broad range of backgrounds, from Physics to Psychology. Mentees can perform in-depth filtering to find mentors who come from similar academic backgrounds, to help answer the age-old question "what do PhDs in X do?"
Companies can also use this information to help them find recruits from a specific field.
Academic skills are gained in academic training - e.g. during a PhD and/or postdoc - and can be leveraged by mentees to identify mentors from similar backgrounds and to build relevant connections.
These data also provide a unique view into the skills landscape that academics gain during their training. As far as we are aware, this is the largest database of its kind.
Providing mentees with access to the various careers that our mentors have chosen in a core element of [re]searching. This alone is a powerful tool to provide an accurate view of available career options.
When combined with skill-based filtering, mentees can ascertain not not only the types of careers that they can pursue, but also the skills used in those jobs. Mentees can use this information to target specific careers, and then upskill in preparation for a career change.
Professional skills are used in non-academic jobs and provide key insight into the relative value different skills hold for different career paths.
Mentees can utilise this information to find careers that rely heavily on particular skills, and upskill in preparation for a career change into a specific industry.