All-provider course timetable

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research

Managing Safely is ideally suited to managers, research supervisors, administrators with safety responsibilities and Departmental Safety Officers across all sectors of the University. It leads to a nationally recognised and accredited training certificate. Please contact the course organiser, Will Hudson (wjh29@admin.cam.ac.uk) for further details before booking on the course.

It is an interactive course that includes state-of-the-art animation in the PowerPoint presentation, work books, DVDs, board games and quizzes, assessments, and a risk assessment project.

Managing Safely is ideally suited to managers, research supervisors, administrators with safety responsibilities and Departmental Safety Officers across all sectors of the University. It leads to a nationally recognised and accredited training certificate. Please contact the course organiser, Will Hudson (wjh29@admin.cam.ac.uk) for further details before booking on the course.

It is an interactive course that includes state-of-the-art animation in the PowerPoint presentation, work books, DVDs, board games and quizzes, assessments, and a risk assessment project.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods.

Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods.

Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research

An introduction to the wide range of resources available at the MML Library and the UL, both in print and online.

How to succeed in your PhD! A one day course which prepares final year PhD students for finishing the writing up, surviving the viva and moving on into postdoc or other employment. All research students in the Graduate School of Life Sciences are expected to attend this highly-recommended course at some point in their final year. The Michaelmas and Easter Term instances are in town and have a bias towards those studying in Biological Sciences; the Lent Term instance is on the Addenbrooke's site and has a bias towards those studying in Clinical Medicine.NB this course replaces both the 'Completing your PhD' and 'FUMO' courses.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods.

Module introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.