Department of Chemistry course timetable
November 2019
Fri 15 |
Chemistry: FS13 LaTex
Finished
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. |
Mon 18 |
Since introduction in 1986 by Binnig, Quate and Gerber, atomic force microscopy (AFM) has emerged as one of the most powerful scanning probe microscopy technique. The possibility to acquire three-dimensional morphology maps of specimens on a surface in both air and in their native liquid environment with sub-nanometre resolution makes it a very versatile single molecule technique. A conventional AFM topography map provides valuable information on the morphology and structure of heterogeneous biological samples, while single molecule force spectroscopy can interrogate the biophysical and nanomechanical properties of the sample at the nanoscale. Furthermore, the combination of AFM with spectroscopic modes enable to enquire the optical properties of the sample with nanoscale resolution. In these introductory lectures, the general capabilities of AFM with respect to other scanning probe and electron microscopy techniques will be discussed. The general principles governing the functioning of AFM in contact and tapping mode will be given, as well as the principles enabling the study of nanomechanical properties of samples by force spectroscopy and nanomechanical imaging. Other modes such as scattering SNOM, AFM-IR and Raman will be generally discussed. The course will provide the necessary background to acquire a morphology map by AFM. The last session will consist of a hand-on session introducing the students to the use and functioning of an AFM instrument. |
Since introduction in 1986 by Binnig, Quate and Gerber, atomic force microscopy (AFM) has emerged as one of the most powerful scanning probe microscopy technique. The possibility to acquire three-dimensional morphology maps of specimens on a surface in both air and in their native liquid environment with sub-nanometre resolution makes it a very versatile single molecule technique. A conventional AFM topography map provides valuable information on the morphology and structure of heterogeneous biological samples, while single molecule force spectroscopy can interrogate the biophysical and nanomechanical properties of the sample at the nanoscale. Furthermore, the combination of AFM with spectroscopic modes enable to enquire the optical properties of the sample with nanoscale resolution. In these introductory lectures, the general capabilities of AFM with respect to other scanning probe and electron microscopy techniques will be discussed. The general principles governing the functioning of AFM in contact and tapping mode will be given, as well as the principles enabling the study of nanomechanical properties of samples by force spectroscopy and nanomechanical imaging. Other modes such as scattering SNOM, AFM-IR and Raman will be generally discussed. The course will provide the necessary background to acquire a morphology map by AFM. The last session will consist of a hand-on session introducing the students to the use and functioning of an AFM instrument. |
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Tue 19 |
Chemistry: CT7 X-Ray Crystallography
Finished
These lectures will introduce the basics of crystallography and diffraction, assuming no prior knowledge. The aim is to provide an overview that will inspire and serve as a basis for researchers to use the Department’s single-crystal and/or powder X-ray diffraction facilities or to appreciate more effectively results obtained through the Department’s crystallographic services. The final lecture will be devoted to searching and visualising crystallographic data using the Cambridge Structural Database system. |
Thu 21 |
Research reproducibility can be hard to get right. The aim of this talk is to raise awareness on the common pitfalls so you can confidently share your work for posterity. We will cover the dos and don’ts of data processing, how to comment on a script, and how to share it. Python will be used as an example because a variety of tools exist for this language. The goal is for anyone reading your paper to be able to go from the raw data to your paper figures. The talk will last 20 minutes and there will be time for questions/discussion afterwards. This talk is brought to you by the Chemistry Data Champions https://www-library.ch.cam.ac.uk/chemistry-data-champions |
Wed 27 |
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. |
Thu 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:
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December 2019
Mon 2 |
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. |
Wed 4 |
Chemistry: FS14 Science Communication: Making Impact with Verbal Presentations with Practical
Finished
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. |
Thu 5 |
Chemistry: CT8 Electron Microscopy
CANCELLED
This lecture will provide an overview of the Department’s electron microscopy facility. It will cover the theory of Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM), including cryo-TEM and tomography, as well as analytical techniques Energy-dispersive X-ray spectroscopy (EDX) and Electron Energy Loss Spectroscopy (EELS). Examples of how these techniques can be used to characterise a range of samples including polymers, proteins and inorganic materials will be shown. |
Fri 6 |
A thorough awareness of issues relating to research ethics and research integrity are essential to producing excellent research. This session will provide an introduction to the ethical responsibilities of researchers at the University, publication ethics and research integrity. It will be interactive, using case studies to better understand key ethical issues and challenges in all areas. There are three sessions running, you need attend only one. |
Thu 12 |
Spectroscopic methods in biochemistry and biophysics are powerful tools to characterise the chemical properties of samples in chemistry and biology, including molecules, macromolecules, living organisms, polymers and materials. Within the wide class of biophysical methods, infrared spectroscopy (IR) is a sensitive analytical label-free tool able to identify the chemical composition and properties of a sample through its molecular vibrations, which produce a characteristic fingerprint spectrum. An infrared spectrum is commonly obtained by passing infrared radiation through a sample and determining what fraction of the incident radiation is absorbed at a particular energy. The energy at which any peak in an absorption spectrum appears corresponds to the frequency of a vibration of a part of a sample molecule. One of the great advantages of infrared spectroscopy is that virtually any sample in virtually any state may be studied, such as liquids, solutions, pastes, powders, films, fibres, gases and surfaces can all be examined. In this introductory course, the basic ideas and definitions associated with infrared spectroscopy will be described. First, the possible configurations of the spectrometers used to measure IR absorption will be discussed. Then, the vibrations of molecules, inorganic and organic chemical compounds, as well as large biomolecules will be introduced, as these are crucial to the interpretation of infrared spectra in every day experimental life. |
January 2020
Tue 14 |
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:
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This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level. In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning. During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced. For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research. |
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Wed 15 |
This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course. |
Drug discovery is a complex multidisciplinary process with chemistry as the core discipline. A small molecule New Chemical Entity (NCE) (80% of drugs marketed) has had its genesis in the mind of a chemist. A successful drug is not only biologically active (the easy bit), but is also therapeutically effective in the clinic – it has the correct pharmacokinetics, lack of toxicity, is stable and can be synthesised in bulk, selective and can be patented. Increasingly, it must act at a genetically defined sub-population of patients. Medicinal chemists therefore work at the centre of a web of disciplines – biology, pharmacology, molecular biology, toxicology, materials science, intellectual property and medicine. This fascinating interplay of disciplines is the intellectual space within which a chemist has to make the key compound that will become an effective medicine. It happens rarely, despite enormous investment in time, money and effort. What factors make a program successful? I would like to briefly outline the process, but importantly to offer some key with examples of success |
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Thu 16 |
This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level. In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning. During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced. For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research. |
Fri 17 |
Drug discovery is a complex multidisciplinary process with chemistry as the core discipline. A small molecule New Chemical Entity (NCE) (80% of drugs marketed) has had its genesis in the mind of a chemist. A successful drug is not only biologically active (the easy bit), but is also therapeutically effective in the clinic – it has the correct pharmacokinetics, lack of toxicity, is stable and can be synthesised in bulk, selective and can be patented. Increasingly, it must act at a genetically defined sub-population of patients. Medicinal chemists therefore work at the centre of a web of disciplines – biology, pharmacology, molecular biology, toxicology, materials science, intellectual property and medicine. This fascinating interplay of disciplines is the intellectual space within which a chemist has to make the key compound that will become an effective medicine. It happens rarely, despite enormous investment in time, money and effort. What factors make a program successful? I would like to briefly outline the process, but importantly to offer some key with examples of success |
Mon 20 |
This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course. |
Tue 21 |
This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level. In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning. During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced. For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research. |
Wed 22 |
This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course. |
This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level. In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning. During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced. For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research. |
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Thu 23 |
This graduate-level course gives an overview of machine learning (ML) techniques that are useful for solving problems in Chemistry, and particularly for the computational understanding and predictions of materials and molecules at the atomic level. In the first part of the course, after taking a quick refresher of the basic concepts in probabilities and statistics, students will learn about basic and advanced ML methods including supervised learning and unsupervised learning. During the second part, the connection between chemistry and mathematical tools of ML will be made and the concepts on the construction of loss functions, representations, descriptors and kernels will be introduced. For the last part, experts who are actively using research methods to solve research problems in chemistry and materials will be invited to give real-world examples on how ML methods have transformed the way they perform research. |
Fri 24 |
When you have 1000s of possible compounds you could make from any one start point what do you make first? This lecture will cover some general basic principles on designing more potent molecules, as well as some practical tips on how to run an optimization program and how to focus synthetic efforts. Binding modalities (reversible, covalent) will be briefly covered, as well as some newer non-traditional modalities. This lecture will also serve as an introduction to the medicinal chemistry game. |
Mon 27 |
This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course. |