Department of Chemistry course timetable
October 2023
Thu 5 |
This session is compulsory for all experimentalists to attend and will provide useful information regarding analytical facilities at this Department including NMR, Mass Spectrometry, X-ray Crystallography, Microanalysis and Electron Microscopy. Short descriptions will be given of all available instruments, as well as explain the procedures for preparing/submitting samples for the analysis will also be discussed. |
November 2023
Wed 1 |
Chemistry: FS15 Creating Publication Quality Figures: Images & Media (In Person, Face to Face)
Finished
The first half of this session will cover an overview of Raytracing versus 3D Modelling, an introduction to the free Raytracing programme Povray, running Povray (command line options). Making and manipulating simple shapes, camera tricks (depth of field, angle of view) and using other software to generate Povray input (e.g. Jmol) The second half of the session is an introduction to 3D modelling and animation using the open source programme Blender. This will cover the installation and customisation of the Blender interface for use with chemical models, how to import chemical structures from Jmol and the protein data base (PDB), the basics of 3D modelling, and an introduction to Key-frame animation. No previous experience with either 3D modelling or animation is required. |
Mon 6 |
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. Once booked you will receive a link to Zoom. |
Fri 10 |
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. Once booked you will receive a link to Zoom. |
Tue 14 |
This series of lectures will support you to improve the standard of your scientific writing. It will be delivered in two parts covering all you need to know about research journals including:
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Fri 17 |
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. Once booked you will receive a link to Zoom. |
Tue 21 |
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. This training is available via Moodle. |
Wed 22 |
The first half of this session will cover an overview of Raytracing versus 3D Modelling, an introduction to the free Raytracing programme Povray, running Povray (command line options). Making and manipulating simple shapes, camera tricks (depth of field, angle of view) and using other software to generate Povray input (e.g. Jmol) The second half of the session is an introduction to 3D modelling and animation using the open source programme Blender. This will cover the installation and customisation of the Blender interface for use with chemical models, how to import chemical structures from Jmol and the protein data base (PDB), the basics of 3D modelling, and an introduction to Key-frame animation. No previous experience with either 3D modelling or animation is required. You will receive a Zoom link when you register for this course |
Thu 30 |
We find ourselves at a pivotal point in history for the long-term sustainability of our society and biome. It would be so easy to have a negative view about the future i.e. climate change is slowly baking us all to death. Last year alone was pretty intense - 1/3 of pakistan was flooded last year and arctic storms ravaged the US. Our climate is becoming more extreme and unpredictable. In 2 years time, we'll be closer to 2050 than the year 2000. We have no time to lose. But this talk isn't about doomerism or trying to induce anxiety in you. It's about demonstrating how you, as a university graduate, highly trained in some technical field, can exert maximum leverage in the fight against climate change through the career choices that you make over the next 10, 20 or 30 years. In this talk, Dr Chadwick will highlight the exciting, state-of-the-art work ongoing around the planet in areas such as Green Hydrogen, The future of food, Carbon Dioxide Removal, Fusion, Fission, and Renewables - technologies all key to our sustainable future. All with the goal of simply providing you with some inspiration and helping you to imagine how your skill sets might one day lend themselves to our collective goal of a sustainable world. Climate change is daunting - but it also represents a massive opportunity to make the world better. Dr Nicholas Chadwick received his MChem in organometallic chemistry from the University of Nottingham in 2012 before successfully studying for a PhD in materials science at University College London in 2015. After graduating he worked on the development of a range of early stage hardware technologies such as advanced transistor technologies, low-cost pollutant sensors for under-represented groups across Southern Asia and Mexico, and carbon capture technologies. He became convinced that direct air carbon capture (DAC) was the one thing we needed at scale to reach our net zero targets of 2050 and didn't have. After going on a bit of a journey scoping out opportunities he decided to co-found Mission Zero Technologies to commercialize and scale Direct Air Capture. |
January 2024
Tue 16 |
You will be introduced to Fortran 90/95 and provided with materials which cover the basics of Fortran 90/95 with an emphasis on applications in the physical sciences. The key concepts of loops, functions, subroutines, modules, and other standard Fortran syntax will be introduced sequentially. |
Mon 22 |
As our understanding of gender identity and sexuality continues to grow, it is up to us as professionals to keep up to date with new language and terminology, as well as maintaining our inclusivity practice in the workplace. This training will provide you with the tools and training needed to create a safe and inclusive professional environment for your staff and students |
Tue 23 |
You will be introduced to Fortran 90/95 and provided with materials which cover the basics of Fortran 90/95 with an emphasis on applications in the physical sciences. The key concepts of loops, functions, subroutines, modules, and other standard Fortran syntax will be introduced sequentially. |
February 2024
Fri 2 |
While leading others is often part of advancing our career – whether inside or outside of academia – often those in leadership positions do not receive training in how to lead and so do it badly. This full-day, practical and pragmatic course introduces participants to four essential ‘elements’ of leadership. In the process of doing so, it explores what leadership is and offers practical tools, strategies and examples to help you begin to lead others more effectively. |
While leading others is often part of advancing our career – whether inside or outside of academia – often those in leadership positions do not receive training in how to lead and so do it badly. This full-day, practical and pragmatic course introduces participants to four essential ‘elements’ of leadership. In the process of doing so, it explores what leadership is and offers practical tools, strategies and examples to help you begin to lead others more effectively. |
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Mon 5 |
Machine Learning for Chemists
Finished
PhDs and Postdocs welcome, no prior knowledge required Machine learning has become a common feature of many scientific papers, including chemistry, biology, and chemical biology. But what does it all mean? In this course, we will investigate the core features of common machine learning techniques such as principal component analysis (PCA), support vector machines (SVMs), and Random Forests, and how these can be applied to a real-world chemistry dataset. This course is meant to serve as a gentle introduction to machine learning - no prior knowledge is required. Emma began her career as an experimental chemist, gaining her PhD in chemoenzymatic total synthesis under the tutelage of Prof. Hans Renata (The Scripps Research Institute, FL). During the course of her doctorate, she gained an interest in machine learning and how it can be applied to help chemists understand their systems. She thus joined the group of Dr. Alpha Lee (University of Cambridge) and later the group of Prof. Matthew Gaunt (University of Cambridge) to hone her expertise in computer programming, algorithm development, and machine learning for chemistry application. |
Engaging communications is important for any audience and vital for communicating research with a public audience. This 2 hour webinar will take you through the art and science for crafting engaging communications including:
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Mon 12 |
Machine Learning for Chemists
Finished
PhDs and Postdocs welcome, no prior knowledge required Machine learning has become a common feature of many scientific papers, including chemistry, biology, and chemical biology. But what does it all mean? In this course, we will investigate the core features of common machine learning techniques such as principal component analysis (PCA), support vector machines (SVMs), and Random Forests, and how these can be applied to a real-world chemistry dataset. This course is meant to serve as a gentle introduction to machine learning - no prior knowledge is required. Emma began her career as an experimental chemist, gaining her PhD in chemoenzymatic total synthesis under the tutelage of Prof. Hans Renata (The Scripps Research Institute, FL). During the course of her doctorate, she gained an interest in machine learning and how it can be applied to help chemists understand their systems. She thus joined the group of Dr. Alpha Lee (University of Cambridge) and later the group of Prof. Matthew Gaunt (University of Cambridge) to hone her expertise in computer programming, algorithm development, and machine learning for chemistry application. |
Tue 13 |
This series of lectures will support you to improve the standard of your scientific writing. It will be delivered in two parts covering all you need to know about research journals including:
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Mon 19 |
Machine Learning for Chemists
Finished
PhDs and Postdocs welcome, no prior knowledge required Machine learning has become a common feature of many scientific papers, including chemistry, biology, and chemical biology. But what does it all mean? In this course, we will investigate the core features of common machine learning techniques such as principal component analysis (PCA), support vector machines (SVMs), and Random Forests, and how these can be applied to a real-world chemistry dataset. This course is meant to serve as a gentle introduction to machine learning - no prior knowledge is required. Emma began her career as an experimental chemist, gaining her PhD in chemoenzymatic total synthesis under the tutelage of Prof. Hans Renata (The Scripps Research Institute, FL). During the course of her doctorate, she gained an interest in machine learning and how it can be applied to help chemists understand their systems. She thus joined the group of Dr. Alpha Lee (University of Cambridge) and later the group of Prof. Matthew Gaunt (University of Cambridge) to hone her expertise in computer programming, algorithm development, and machine learning for chemistry application. |
Mon 26 |
Machine Learning for Chemists
Finished
PhDs and Postdocs welcome, no prior knowledge required Machine learning has become a common feature of many scientific papers, including chemistry, biology, and chemical biology. But what does it all mean? In this course, we will investigate the core features of common machine learning techniques such as principal component analysis (PCA), support vector machines (SVMs), and Random Forests, and how these can be applied to a real-world chemistry dataset. This course is meant to serve as a gentle introduction to machine learning - no prior knowledge is required. Emma began her career as an experimental chemist, gaining her PhD in chemoenzymatic total synthesis under the tutelage of Prof. Hans Renata (The Scripps Research Institute, FL). During the course of her doctorate, she gained an interest in machine learning and how it can be applied to help chemists understand their systems. She thus joined the group of Dr. Alpha Lee (University of Cambridge) and later the group of Prof. Matthew Gaunt (University of Cambridge) to hone her expertise in computer programming, algorithm development, and machine learning for chemistry application. |
Wed 28 |
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. |
March 2024
Mon 4 |
Machine Learning for Chemists
Finished
PhDs and Postdocs welcome, no prior knowledge required Machine learning has become a common feature of many scientific papers, including chemistry, biology, and chemical biology. But what does it all mean? In this course, we will investigate the core features of common machine learning techniques such as principal component analysis (PCA), support vector machines (SVMs), and Random Forests, and how these can be applied to a real-world chemistry dataset. This course is meant to serve as a gentle introduction to machine learning - no prior knowledge is required. Emma began her career as an experimental chemist, gaining her PhD in chemoenzymatic total synthesis under the tutelage of Prof. Hans Renata (The Scripps Research Institute, FL). During the course of her doctorate, she gained an interest in machine learning and how it can be applied to help chemists understand their systems. She thus joined the group of Dr. Alpha Lee (University of Cambridge) and later the group of Prof. Matthew Gaunt (University of Cambridge) to hone her expertise in computer programming, algorithm development, and machine learning for chemistry application. |
Wed 6 |
Have you ever struggled with styles of communication of others (peers, lecturers, supervisors, staff), wondered why some people seem to use more formal language, or be more direct than others? Culture plays a big part in how we communicate, and adjusting to the cultural communication norms means more than learning a foreign language. In Cambridge's diverse and multicultural environment, we constantly communicate with people whose cultural communication norms differ from ours, whether you are a native English speaker from the United Kingdom, a native English speaker from elsewhere in the world, or have learnt English as a foreign language. In order to avoid misunderstanding, or worse still, conflict, brought on by variations in communication styles we need to learn to make allowances for the cultural differences in how people communicate. To better understand cross-cultural complexity and increase your awareness of cultural identities, come to a session on intercultural communication to increase your cultural awareness and give you a better understanding of how culture may affect your everyday communication. |
Introduction to Public Engagement
Finished
Training for PhD students: Public engagement is increasingly seen as an important part of any research career, with the potential to give you the skills and insight to improve your research, make it more relevant and have impact. Rather than trying to engage with everyone, we’ll help you explore why you want to engage and who it would be valuable for you to have conversations with, and how, and where. We’ll introduce a logic model way of planning public engagement and sign post you to further training, support, advice and platforms for engagement across the University. |
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Tue 12 |
Trainer: Oleksandra Korychenska from Cambridge enterprise What is Intellectual Property (IP)? Why does it matter to you? Who owns it? Who benefits? What is consultancy? What is a spin out? Why would you want to commercialise results from your research? What is it anyway? All this, and more, will be covered in a one-hour presentation by Cambridge Enterprise on the 12th of March. It is aimed at postgraduate students in Chemistry, after feedback showed that they would like to learn more about research commercialisation and IP. However, anybody is welcome to attend! |