Department of Chemistry course timetable

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.

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.

A ‘recommended’ optional course for Chemistry graduates that introduces all the relevant online databases available to you in the university: citation databases such as Web of Science, Scopus, and PubMed, which index all the scientific literature that is published, as well as chemistry and related subject-specific databases. You will be guided on how to search citation databases effectively and the session includes a hands-on element where you can practice - please bring your own laptop.

The session will be most suitable for those who are new to searching citation databases or would like a refresher.

Please note that this session will not cover searching the databases Reaxys and SciFinder. These are covered by IS5.

Please bring your own laptop so you can participate in the practical element of the session.

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.

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.

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.

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.

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!

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.

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.

Submission of the PhD thesis can seem to be a daunting experience, from constructing it to submitting and then being examined, with one of those examiners coming from an external institution. In this session, Marie Dixon (Degree Committee Office, School of Physical Sciences), Rachel MacDonald and Deborah Longbottom will talk through all aspects of procedure regarding thesis submission and answer any questions students wish to pose. Students who were recently examined, as well as members of academic staff who carry out PhD vivas will also be there to talk about the reality of the process from all perspectives

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.

Submission of an MPhil thesis can seem to be a daunting experience, from constructing it to submitting and then being examined, with one of those examiners coming from an external institution. In this session, Marie Dixon (Degree Committee Office, School of Physical Sciences), Rachel MacDonald and Deborah Longbottom will talk through all aspects of procedure regarding thesis submission and answer any questions students wish to pose. Students who were recently examined, as well as members of academic staff who carry out MPhil vivas will also be there to talk about the reality of the process from all perspectives.

Submission of the first year report can seem to be a daunting experience, from constructing it to submitting and then being assessed by academic staff. In this session, Marie Dixon (Degree Committee Office, School of Physical Sciences), Rachel MacDonald and Deborah Longbottom will talk through all aspects of procedure and answer any questions students wish to pose. Students who went through the first year exam in 2016, as well as members of academic staff who carry out first year vivas will also be there to talk about the reality of the process from all perspectives.

For FS17 PhD Thesis Submission and the viva Experience: https://www.training.cam.ac.uk/event/2237472

For FS18 MPhil Thesis Submission and the viva Experience: https://www.training.cam.ac.uk/event/2316740

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.

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.

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.

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.

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.

This hands-on course teaches the basics of Latex including syntax, lists, maths equations, basic chemical equations, tables, graphical figures and internal and external referencing. We also learn how to link documents to help manage large projects. The course manual is presented in the style of a thesis and since you also receive the source code you also receive a template for a thesis.

The overall scope of this course is to provide an all-inclusive view of the importance of physicochemical properties in the design and development of drugs, delivered to patients by oral administration. In particular, it gives ample information on the importance of the role played by the solubility and the permeability of orally administered drug substances in influencing their rate of absorption and systemic circulation.