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Graduate School of Life Sciences course timetable

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Thu 29 Oct – Fri 26 Feb 2021

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November 2020

Wed 4

Museums and collections are so much more than the objects they house. They are places of research, education and engagement, and they are open to members of the public in ways that departments and colleges are not. They can allow researchers to reach a range of diverse audiences. This training session will give you an insight into working with museums. The session will be delivered with the University of Cambridge Museums.

Mon 9
Core Statistics (1 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

Tue 10

This course gives an introduction into how to engage with the public through media. It will cover the differing types of media, what makes research newsworthy, how to work with the communications office to gain media coverage, what to expect from an interview (print, pre-recorded, live) and how to communicate well in interviews. It will be delivered jointly with the University Communications team

Wed 11
Core Statistics (2 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

This course will give an introduction to Public and Patient Involvement. You will find out about local support available in the region to help plan, deliver and build PPI into research, that will improve research for patients and services users and carers. This course will be delivered by Dr Amanda Stranks, PPI/E and Communications Strategy Lead NIHR Cambridge BRC Communications and PPI/E Department.

Thu 12

This course will cover how to use Social Media tools for Public Engagement. The course will be delivered by the Social Media and AV team.

Mon 16
Core Statistics (3 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

The Engaged Researcher Online Training: Creative Writing new (1 of 2) Finished 10:00 - 11:30 Online

Join Forward Prize nominee David Cain (2019), for a training session that explores responses to research through creative writing. This training will develop creative ways by which you can engage with new and existing audiences, enabling you to be more confident in developing, and sharing, creative writing responses to your area of research.

The session will introduce creative writing for poetry and prose, and textual writing for exhibition / display. It will also discuss formats for delivery / performance.

Wed 18
Core Statistics (4 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

Fri 20
The Engaged Researcher Online Training: Creative Writing new (2 of 2) Finished 10:00 - 11:00 Online

Join Forward Prize nominee David Cain (2019), for a training session that explores responses to research through creative writing. This training will develop creative ways by which you can engage with new and existing audiences, enabling you to be more confident in developing, and sharing, creative writing responses to your area of research.

The session will introduce creative writing for poetry and prose, and textual writing for exhibition / display. It will also discuss formats for delivery / performance.

Mon 23
Core Statistics (5 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

Wed 25
Core Statistics (6 of 6) Finished 10:00 - 13:00 GSLS Online Live Training

PLEASE NOTE that this course will be taught live online, with demonstrators available to help you throughout if have any questions. All lecture components will be recorded and uploaded to the course Moodle page so that you will be able to access that information even if technical or time zone restrictions means that you aren't able to join us for the live sessions.

This virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R or Python software environments. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R or Python confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

Both R and Python are free software environments that are suitable for statistical and data analysis.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R or Python and moreover know when, and when not, to apply these techniques.

December 2020

Tue 15

This training is for those whose research involves the use of animals in research, and who want to feel more confident to talk about it with those outside the lab. This training will be run by Understanding Animal Research.

January 2021

Mon 25

We’ll be looking at the what, why and how of public engagement and introducing researchers to some of the ways to plan an effective public engagement project. Topics: • The what: definitions of public engagement, who are the public, what activities count as engagement, what are the goals? • The why: University commitment to PE, REF, Funders • The how: the Logic Model approach to planning PE, practical considerations, moving engagement online and opportunities at the University.

Course structure: Monday 10am-11am: Introduction to PE Wednesday 2pm-3pm: Evaluation and online PE tips and hints and opportunities at the University Friday 10am-12pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

Wed 27

We’ll be looking at the what, why and how of public engagement and introducing researchers to some of the ways to plan an effective public engagement project. Topics: • The what: definitions of public engagement, who are the public, what activities count as engagement, what are the goals? • The why: University commitment to PE, REF, Funders • The how: the Logic Model approach to planning PE, practical considerations, moving engagement online and opportunities at the University.

Course structure: Monday 10am-11am: Introduction to PE Wednesday 2pm-3pm: Evaluation and online PE tips and hints and opportunities at the University Friday 10am-12pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

Fri 29

We’ll be looking at the what, why and how of public engagement and introducing researchers to some of the ways to plan an effective public engagement project. Topics: • The what: definitions of public engagement, who are the public, what activities count as engagement, what are the goals? • The why: University commitment to PE, REF, Funders • The how: the Logic Model approach to planning PE, practical considerations, moving engagement online and opportunities at the University.

Course structure: Monday 10am-11am: Introduction to PE Wednesday 2pm-3pm: Evaluation and online PE tips and hints and opportunities at the University Friday 10am-12pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

February 2021

Mon 8
The Engaged Researcher Online: Research Storytelling (1 of 3) [Full] 14:00 - 15:30 Online

Capturing your audience’s attention and keeping it is vital for any type of public engagement. Having a good story to tell and then telling it in a compelling way enables you to connect with a wide audience. This module takes you through the art and science of storytelling: exploring attention and motivation, dramatic structure, rhetorical devices, visual enhancements, and peripheral influences so that you can craft your own engaging story.

Wed 10
The Engaged Researcher Online: Research Storytelling (2 of 3) [Full] 09:00 - 10:00 Online

Capturing your audience’s attention and keeping it is vital for any type of public engagement. Having a good story to tell and then telling it in a compelling way enables you to connect with a wide audience. This module takes you through the art and science of storytelling: exploring attention and motivation, dramatic structure, rhetorical devices, visual enhancements, and peripheral influences so that you can craft your own engaging story.

Fri 12
The Engaged Researcher Online: Research Storytelling (3 of 3) [Full] 14:30 - 15:30 Online

Capturing your audience’s attention and keeping it is vital for any type of public engagement. Having a good story to tell and then telling it in a compelling way enables you to connect with a wide audience. This module takes you through the art and science of storytelling: exploring attention and motivation, dramatic structure, rhetorical devices, visual enhancements, and peripheral influences so that you can craft your own engaging story.

Mon 15

Successful engagement with the public can benefit research, researchers and the public – but how do you go about demonstrating this change? Evaluation of engagement doesn’t just help us demonstrate the value of our PE initiatives but can help bring us closer to our audiences by giving the public a strong clear voice. This workshop will guide you through the best evaluation processes showing you When, Why and crucially How to use evaluation to give you reliable and clear data. Demonstrate success to funders; record Impact for REF; learn how to improve your processes and have a better understanding of the people you are connecting with. This course is going to be run by Jamie Galagher: Jamie is an award-winning freelance science communicator and engagement professional. He has delivered training around the world, from skyscrapers of Hong Kong to tents in the African bush. Having had four years’ experience as the central PE lead for the University of Glasgow he has worked on improving the reach, profile and impact of research engagement in almost every academic discipline. Specialising in evaluation Jamie provides consultancy services to charities and universities helping them to demonstrate their impact and understand their audiences and stakeholders. Jamie is also an associate editor of the Research for All journal. He was named as one of the “100 leading practising scientists in the UK” by the Science Council and as one of the “175 Faces of Chemistry” by the Royal Society of Chemistry. He won the International 3 Minute Thesis Competition and Famelab Scotland. www.jamiebgall.co.uk @jamiebgall

Tue 16

Successful engagement with the public can benefit research, researchers and the public – but how do you go about demonstrating this change? Evaluation of engagement doesn’t just help us demonstrate the value of our PE initiatives but can help bring us closer to our audiences by giving the public a strong clear voice. This workshop will guide you through the best evaluation processes showing you When, Why and crucially How to use evaluation to give you reliable and clear data. Demonstrate success to funders; record Impact for REF; learn how to improve your processes and have a better understanding of the people you are connecting with. This course is going to be run by Jamie Galagher: Jamie is an award-winning freelance science communicator and engagement professional. He has delivered training around the world, from skyscrapers of Hong Kong to tents in the African bush. Having had four years’ experience as the central PE lead for the University of Glasgow he has worked on improving the reach, profile and impact of research engagement in almost every academic discipline. Specialising in evaluation Jamie provides consultancy services to charities and universities helping them to demonstrate their impact and understand their audiences and stakeholders. Jamie is also an associate editor of the Research for All journal. He was named as one of the “100 leading practising scientists in the UK” by the Science Council and as one of the “175 Faces of Chemistry” by the Royal Society of Chemistry. He won the International 3 Minute Thesis Competition and Famelab Scotland. www.jamiebgall.co.uk @jamiebgall

Mon 22

Children are our next generation of researchers and as an audience for Research Engagement, they can be both rewarding and challenging. More than ever, online content plays an important role in reaching and inspiring children of different age groups for research. With so much content already out there how to make new and relevant content online? What are parents and teachers looking for? What safeguarding considerations should you have? This course will aim to answer these and other questions and provide guidance in creating content.

Monday session 1: - Introduction to producing engaging online content with children and instructions on how to develop the project throughout the week. Wednesday Session 2: - Mentoring time for questions or one-on-one advise. Friday Session 3: - showcase of the projects.

Tue 23

This session aims to give you tools to manage your relationships with business and industry, charities, and other non-academic partners. The session is suitable for researchers and facilitators looking to future-proof their impact partnerships and co-creation relationships. We will use case studies from the arts, humanities and social sciences.

We’ll cover the basics of intellectual property management, licensing of co-created resources and research outputs, and academic consultancy. Above all we want to support you to ensure a sustainable, fair, future-proof foundation for scalable real-world impact.

The sessions on Friday, 26 February and Monday, 1 March gives the opportunity to the participants to have a 30 minute 1:1 session with the trainers to discuss issues and queries relating to their own project.

Wed 24

Children are our next generation of researchers and as an audience for Research Engagement, they can be both rewarding and challenging. More than ever, online content plays an important role in reaching and inspiring children of different age groups for research. With so much content already out there how to make new and relevant content online? What are parents and teachers looking for? What safeguarding considerations should you have? This course will aim to answer these and other questions and provide guidance in creating content.

Monday session 1: - Introduction to producing engaging online content with children and instructions on how to develop the project throughout the week. Wednesday Session 2: - Mentoring time for questions or one-on-one advise. Friday Session 3: - showcase of the projects.

Fri 26

This session aims to give you tools to manage your relationships with business and industry, charities, and other non-academic partners. The session is suitable for researchers and facilitators looking to future-proof their impact partnerships and co-creation relationships. We will use case studies from the arts, humanities and social sciences.

We’ll cover the basics of intellectual property management, licensing of co-created resources and research outputs, and academic consultancy. Above all we want to support you to ensure a sustainable, fair, future-proof foundation for scalable real-world impact.

The sessions on Friday, 26 February and Monday, 1 March gives the opportunity to the participants to have a 30 minute 1:1 session with the trainers to discuss issues and queries relating to their own project.

Children are our next generation of researchers and as an audience for Research Engagement, they can be both rewarding and challenging. More than ever, online content plays an important role in reaching and inspiring children of different age groups for research. With so much content already out there how to make new and relevant content online? What are parents and teachers looking for? What safeguarding considerations should you have? This course will aim to answer these and other questions and provide guidance in creating content.

Monday session 1: - Introduction to producing engaging online content with children and instructions on how to develop the project throughout the week. Wednesday Session 2: - Mentoring time for questions or one-on-one advise. Friday Session 3: - showcase of the projects.