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Department of Chemistry

Department of Chemistry course timetable

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Sat 16 Feb – Wed 5 Jun

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February 2019

Wed 20
Machine Learning & Artificial Intelligence for Chemists new (2 of 7) In progress 12:00 - 13:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

Wed 27
Machine Learning & Artificial Intelligence for Chemists new (3 of 7) In progress 12:00 - 13:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

March 2019

Fri 1
IS5 SciFinder and Reaxys [Places] 11:30 - 13:00 Todd-Hamied

A ‘recommended’ optional course introducing electronic databases SciFinder and Reaxys presented by Professor Jonathan Goodman comprising of presentation followed by hands-on investigation.

Please bring your own laptop for the practical element of the session.

Personal registration required for access to SciFinder. Please see the prerequisites.

Wed 6
Machine Learning & Artificial Intelligence for Chemists new (4 of 7) In progress 11:00 - 13:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

Tue 12
Machine Learning & Artificial Intelligence for Chemists new (5 of 7) In progress 12:00 - 13:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

Fri 15
FS11 Scientific Writing: From Pain to Pleasure [Places] 12:00 - 13:00 Unilever Lecture Theatre

Much of scientific knowledge and information is communicated in written form, be it via journal publications, theses or in other media. However, scientific writing differs from other styles of writing quite significantly, with regard to structure, grammar and word choice. This lecture will outline the basics of what to consider when 'writing science', in order to smoothen the path to your first peer-reviewed publication, as well as your later thesis.

Mon 18
IS3 Research Information Skills for Graduate Students [Places] 09:00 - 11:00 Unilever Lecture Theatre

This compulsory course will equip you with the skills required to manage the research information you will need to gather throughout your graduate course, as well as the publications you will produce yourself. It will also help you enhance your online research profile and measure the impact of research.

Wed 20
Machine Learning & Artificial Intelligence for Chemists new (6 of 7) In progress 12:00 - 13:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

Fri 22

This compulsory session introduces Research Data Management (RDM) to Chemistry PhD students. It is highly interactive and utilises practical activities throughout.

Key topics covered are:

  • Research Data Management (RDM) - what it is and what problems can occur with managing and sharing your data.
  • Data backup and file sharing - possible consequences of not backing up your data, strategies for backing up your data and sharing your data safely.
  • Data organisation - how to organise your files and folders, what is best practice.
  • Data sharing - obstacles to sharing your data, benefits and importance of sharing your data, the funder policy landscape, resources available in the University to help you share your data.
  • Data management planning - creating a roadmap for how not to get lost in your data!

Refreshments are included for this course

Mon 25
FS4 Unconscious Bias [Places] 15:00 - 16:30 Wolfson Lecture Theatre

Unconscious Bias refers to the biases we hold that are not in our conscious control. Research shows that these biases can adversely affect key decisions in the workplace. The session will enable you to work towards reducing the effects of unconscious bias for yourself and within your organisation. Using examples that you will be able to relate to, we help you to explore the link between implicit bias and the impact on the organisation. The overall aim of the session is to provide participants with an understanding of the nature of Unconscious Bias and how it impacts on individual and group attitudes, behaviours and decision-making processes.

Wed 27
Machine Learning & Artificial Intelligence for Chemists new (7 of 7) In progress 12:00 - 14:00 Todd-Hamied

Artificial Intelligence (AI) in the context of chemistry has a long history. The first application was in mass spectrometry, but AI is now being applied to a diverse range of problems, including reaction prediction and drug discovery. Machine learning (ML) is an important part of AI, and the aim of this course is to introduce some of the main ML concepts and techniques, and to illustrate their use in contemporary chemical applications. By the end of the course, you should be able to judge which of these ML techniques are appropriate for a given task and evaluate the results.

April 2019

Wed 3

The main aim of giving a presentation to the public or a science venue is to present information in a way that the audience will remember at a later time. There are several ways in which we can improve this type of impact with an audience. This interactive lecture explores some of those mechanisms.

Fri 5

The main aim of giving a presentation to the public or a science venue is to present information in a way that the audience will remember at a later time. There are several ways in which we can improve this type of impact with an audience. This interactive lecture explores some of those mechanisms.

This session will require 4-5 volunteers to provide a 10 min talk which the session will show how to improve. Presenters in the following week's Peer to Peer presentations will be given priority booking for this event.

Tue 30
IS1 Chemistry Library Orientation [Places] 14:15 - 14:45 Library

This is a compulsory session which introduces new graduate students to the Department of Chemistry Library and its place within the wider Cambridge University Library system. It provides general information on what is available, where it is, and how to get it. Print and online resources are included.

You must choose one session out of the 9 sessions available.

May 2019

Tue 7
CP1 Career options for PhDs [Places] 11:00 - 14:30 Unilever Lecture Theatre

PhD students have plenty of options once you graduate. In this interactive session we will look at the pros and cons of different career options. You will have a chance to think about what you want your work to do for you and what you can offer employers, and you will learn ways to find out more about jobs in which you are interested.

Tue 14
FS9 A Practical Introduction to Computational Organic Chemistry [Places] 10:00 - 12:00 Unilever Lecture Theatre

The combination of modern computing power and density functional theory (DFT) has made it possible to explore the mechanisms and catalytic cycles of complex organic and organometallic reactions. These lectures will provide a practical introduction to performing DFT calculations to elucidate reaction mechanisms. Other applications of DFT calculations will be discussed such as computing spectra and structure identification.

These lectures will be accompanied by a workshop that will show the user how to perform DFT calculations and how to use the data generated by these calculations to draw conclusions about reaction mechanisms. No prior computational experience is required.

Wed 15

These are the accompanying workshops that will show the user how to perform DFT calculations and how to use the data generated by these calculations to draw conclusions about reaction mechanisms. No prior computational experience is required.

Tue 21
CP2 Successful job applications and selections for PhDs [Places] 11:00 - 14:30 Unilever Lecture Theatre

Starting to apply for jobs both in and outside academia? Preparing for an interview? Not sure how to target your application, what to include and what to leave out. In this session you can learn more about how selection processes work including how to put together a CV and cover letter and how to prepare for job interviews. The workshop will include interactive exercises, a review of successful application materials, and discussions.

Thu 23
FS1 Successful Completion of a Research Degree & FS2 Dignity@Study [Places] 12:00 - 13:30 Unilever Lecture Theatre

FS1 - Successful Completion of a Research Degree An hour devoted to a discussion of how to plan your time effectively on a day to day basis, how to produce a dissertation/thesis (from first year report to MPhil to PhD) and the essential requirements of an experimental section.

FS2 - Dignity@Study The University of Cambridge is committed to protecting the dignity of staff, students, visitors to the University, and all members of the University community in their work and their interactions with others. The University expects all members of the University community to treat each other with respect, courtesy and consideration at all times. All members of the University community have the right to expect professional behaviour from others, and a corresponding responsibility to behave professionally towards others. Nick will explore what this means for graduate students in this Department and the session will conclude with tea/coffee and biscuits, in order to provide an opportunity to ask questions more informally.

This is a compulsory session for 1st year post-graduates.

Tue 28

This compulsory session introduces Research Data Management (RDM) to Chemistry PhD students. It is highly interactive and utilises practical activities throughout.

Key topics covered are:

  • Research Data Management (RDM) - what it is and what problems can occur with managing and sharing your data.
  • Data backup and file sharing - possible consequences of not backing up your data, strategies for backing up your data and sharing your data safely.
  • Data organisation - how to organise your files and folders, what is best practice.
  • Data sharing - obstacles to sharing your data, benefits and importance of sharing your data, the funder policy landscape, resources available in the University to help you share your data.
  • Data management planning - creating a roadmap for how not to get lost in your data!

Refreshments are included for this course

Thu 30
IS3 Research Information Skills [Places] 09:00 - 11:00 Unilever Lecture Theatre

This compulsory course will equip you with the skills required to manage the research information you will need to gather throughout your graduate course, as well as the publications you will produce yourself. It will also help you enhance your online research profile and measure the impact of research.

A short break for refreshments will be included

June 2019

Wed 5
FS9 Computational Organic Chemistry Workshop Not bookable 10:00 - 12:00 G30

These are the accompanying workshops that will show the user how to perform DFT calculations and how to use the data generated by these calculations to draw conclusions about reaction mechanisms. No prior computational experience is required.