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Graduate School of Life Sciences course timetable

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Wed 8 Apr – Mon 18 May

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Wednesday 8 April

12:30
FOCUS GROUP: Is Entrepreneurship and Enterprise at Cambridge Working for you? new CANCELLED 12:30 - 13:30 Student Services Centre, Exams Hall, Room AG03b

We are running a series of focus groups to gain a better understanding of the entrepreneurship and enterprise landscape at Cambridge for STEMM postgraduates. We welcome everyone to come along and share their experiences and thoughts about this subject with us. Whether you have previously gained entrepreneurship and enterprise experience or thought this is an area to build on as part of your post graduate training, your contribution to these sessions would be most valuable.

Lunch will be provided as a thank you for your time and contribution.

Thursday 9 April

10:00
The Engaged Researcher: Famelab heats new (2 of 2) CANCELLED 10:00 - 13:00 Postdoc Centre@ Mill Lane, Eastwood Room

Hundreds of science communicators across the UK go head to head every year to become the FameLab UK champion. Are you interested in… Improving your communication skills, talking about your research with a public audience, joining a global network of science communicators and an all-expenses paid trip to Cheltenham Science Festival?

Please register to this event here: https://cheltenhamfestivals.wufoo.com/forms/x1rkhi9l0lsbx3e/

Monday 20 April

12:30
FOCUS GROUP: Is Entrepreneurship and Enterprise at Cambridge Working for you? new CANCELLED 12:30 - 13:30 Student Services Centre, Meeting Room CG18

We are running a series of focus groups to gain a better understanding of the entrepreneurship and enterprise landscape at Cambridge for STEMM postgraduates. We welcome everyone to come along and share their experiences and thoughts about this subject with us. Whether you have previously gained entrepreneurship and enterprise experience or thought this is an area to build on as part of your post graduate training, your contribution to these sessions would be most valuable.

Lunch will be provided as a thank you for your time and contribution.

Thursday 23 April

10:00
The Engaged Researcher: Working with Museums new CANCELLED 10:00 - 13:00 Postdoc Centre@ Mill Lane, Seminar Room

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 the breadth of activity ongoing at University of Cambridge Museums and how it could relate to your research and public engagement plans. After this training you will have a better understanding of the opportunities to work with museums.

Tuesday 28 April

09:30
How to write an academic paper and get it published (Life Sciences) CANCELLED 09:30 - 16:30 Postdoc Centre@ Mill Lane, Seminar Room

The course takes an evidence-based approach to writing. Participants will learn that publishing is a game and the more they understand the rules of the game the higher their chances of becoming publishing authors. They will learn that writing an academic article and getting it published may help with their careers but it does not make them better researchers, or cleverer than they were before their paper was accepted; it simply means they have played the game well.

Suitable for GSLS postgraduates in any discipline who are keen to learn how to write academic papers and articles efficiently as well as more established researchers who have had papers rejected and are not really sure why.

If you want a better chance of your name on a paper, this is for you!

Trainer

Olivia Timbs is an award-winning editor and journalist with over 30 years' experience gained from working on national newspapers and for a range of specialist health and medical journals.

10:00
Understanding Open Data new CANCELLED 10:00 - 12:00 Postdoc Centre@ Mill Lane, Eastwood Room

Conclusions without supporting data are just claims. More and more researchers are sharing their data to improve reproducibility, get more citations and spark collaborations, yet the process can be daunting. We will explore the benefits of sharing data, as well as any concerns you might have, and give you practical tips and tools to ensure that you make the most of the opportunity to open up your data for the world.

Monday 4 May

10:00

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 10am-11am: Evaluation and online PE tips and hints and opportunities at the University Thursday 2pm-4pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

14:00
Core Statistics (1 of 6) Finished 14:00 - 17:00 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.

15:30
Engaged Researcher: Masterclass - Working with funding bodies new Finished 15:30 - 17:00 UIS Online Courses - instructor-led

Money, money, money… Securing funding for Public Engagement projects is as a struggle professional staff and researchers are often all too familiar with. Understanding the perspective of the funding bodies can help to increase your success rates and to build up long-term collaborations with the funders. Dr Rebecca Jones, Public Engagement Manager at the Cambridge Wellcome Stem Cell Institute and former PE Manager for Wellcome trust, will share her experience from working on both sides of the equation. The session is aimed at professional staff and researchers working on public engagement funding applications or pathways to impact sections. This training is now going to be on MS teams: Email dam74@cam.ac.uk if you'd like to take part.

Wednesday 6 May

10:00

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 10am-11am: Evaluation and online PE tips and hints and opportunities at the University Thursday 2pm-4pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

14:00
Core Statistics (2 of 6) Finished 14:00 - 17:00 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.

Thursday 7 May

14:00

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 10am-11am: Evaluation and online PE tips and hints and opportunities at the University Thursday 2pm-4pm: Do you have any questions? 1:1 advice sessions (not mandatory to attend!)

Monday 11 May

09:30
Innovation and Enterprise - a commercial perspective new CANCELLED 09:30 - 16:30 Postdoc Centre@ Mill Lane, Eastwood Room

Provides an understanding of the UK and European landscape for researchers in the context of future careers and collaborations with industry. Also valuable for academics looking for a career move into industry. Provides an insight into what innovation really means and introduces the practical project management tools to implement innovative projects.

10:00
Profile-Raising and Networking new CANCELLED 10:00 - 16:00 Postdoc Centre@ Mill Lane, Seminar Room

This whole day session is designed to help researchers develop strategies for making networking part of a successful career, whether inside or outside of research. It focuses on thinking about all of the researchers' working life as a route to networking, rather than being a course about "personal impact" in conference coffee breaks.

14:00
Core Statistics (3 of 6) Finished 14:00 - 17:00 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.

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.

Tuesday 12 May

09:00

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.

Wednesday 13 May

09:00

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.

14:00
Core Statistics (4 of 6) Finished 14:00 - 17:00 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.

Thursday 14 May

09:00

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.

Friday 15 May

10:00
Problem Solving and Innovation in a Research intensive Environment new CANCELLED 10:00 - 16:00 Postdoc Centre@ Mill Lane, Eastwood Room

This course has been designed to help graduates students and ECRs to develop their understanding of available tools and techniques which can aid with problem solving and innovation in a research-intensive environment.

14:30

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.

Monday 18 May

09:30
The Engaged Researcher: Animate your research new CANCELLED 09:30 - 12:30 Postdoc Centre@ Mill Lane, Eastwood Room

This course will give you an introduction to visual tools to make your research more accessible and engaging. It is all about breaking down barriers and to empower researchers and professional staff to engage well. This is often about finding a visual link for complex content. This session is going to be delivered by Dr ALina Loth, a Public Engagement professional and Illustrator (http://www.engagedart.uk/)

10:00

Animations can be a powerful tool to convey a message and to capture your audiences attention and interest. By bringing movement into your visualisation you add a new dimension to your visual storytelling and the process can be incredibly creative. This course will introduce you to a range of animation techniques using simple techniques to get you started on animating your own research. No previous knowledge or special equipment required.

Monday session 1: - Introduction to animation with instructions on how to work on your own animation throughout the week

Wednesday Session 2: - Mentoring time for questions or one-on-one advise

Friday Session 3: - showcase and presentation of the produced animations

12:30
FOCUS GROUP: Is Entrepreneurship and Enterprise at Cambridge Working for you? new CANCELLED 12:30 - 13:30 Postdoc Centre@ Mill Lane, Seminar Room

We are running a series of focus groups to gain a better understanding of the entrepreneurship and enterprise landscape at Cambridge for STEMM postgraduates. We welcome everyone to come along and share their experiences and thoughts about this subject with us. Whether you have previously gained entrepreneurship and enterprise experience or thought this is an area to build on as part of your post graduate training, your contribution to these sessions would be most valuable.

Lunch will be provided as a thank you for your time and contribution.

14:00
Core Statistics (5 of 6) Finished 14:00 - 17:00 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.