Department of Chemistry course timetable
February 2024
| 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. |
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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. |
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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! |
| Wed 13 |
AI Clinic – The Accelerate Programme
Finished
Have you thought about using AI in your research but aren’t sure how to get started? Or are you already using AI and have run into challenges with implementation? Come and meet the Accelerate team to find the support you need. The Accelerate Programme, based in the Department of Computer Science and Technology, are holding an in-person AI Clinic Session on Wednesday 13th March from 11am – 1pm in the Todd-Hamied room of the Chemistry Department. The clinic is open to support all staff and students with AI research. No matter your level of experience with AI, we invite you to come and talk to our team. We support projects at all stages - from ideation, grant writing and data gathering, through to software issues and publication. The clinic is running as a drop-in session, but we also have a form if you'd like to share details of your issue in advance. We look forward to meeting you there! |
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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 |
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| Thu 14 |
This session introduces three citation databases: Web of Science, Scopus, and PubMed (if relevant to the audience). These databases index all the scientific literature that is published. When used efficiently, and in combination, they are a powerful tool for finding the research publications you need - so you don't miss out on anything. They will be compared and contrasted with each other, and with using Google or Google Scholar, to find citations. You will be guided on how to search these databases effectively; the session includes a hands-on element where you can practice. The session covers how to set up email alerts for searches and citations, so you can keep up with research published in your field. It also covers how to find metrics and altmetrics available for a journal, journal article, or author, so you can evaluate the quality of a piece of research, or a particular author's research before collaborating with them, for example. It will cover how to export the citations you find to your reference manager so you can easily create a bibliography and/or cite publications in your own work. The session will be most suitable for those who are new to searching citation databases or would like a refresher. |
April 2024
| Wed 17 |
A Scientific Editor from the Royal Society of Chemistry’s flagship journal Chemical Science will be talking about careers in scientific publishing, specifically focused on journals publishing, including her own career journey, what is involved in her role and an overview of the RSC and Chemical Science. The session will include an opportunity for questions about anything relating to scientific publishing in general, or specifically relating to the topic of the talk. |
| Mon 22 |
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, a member of the Degree Committee Office, School of Physical Sciences, a member of the PG Education team and an academic 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. |
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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, a member of the Degree Committee Office, School of Physical Sciences, a member of the PG Education team and an academic will talk through all aspects of procedure and answer any questions students wish to pose. Students who went through their first year exam, 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. |
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Chemistry: FS17 PhD Thesis Submission and the Viva Experience for Chemists (In Person, Face to Face)
Finished
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, a member of the Degree Committee Office, School of Physical Sciences, a member of the PG Education team and an academic 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 |
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| Tue 23 |
This is a practical skills-based course which comprises of 1 optional drop-in session and 6 compulsory instructor-lead statistics sessions. These will take place in Todd Hamied |
| Wed 24 |
Chemistry: Philosophy for Physical Scientists
In progress
Science is a strikingly successful and powerful feature of contemporary human cultures: it has transformed lives, enabled great technological feats and often revealed the world to be a much stranger place than appearances suggest. But what is science, really, and how and why has it been so successful? |
| Tue 30 |
This is a practical skills-based course which comprises of 1 optional drop-in session and 6 compulsory instructor-lead statistics sessions. These will take place in Todd Hamied |
May 2024
| Wed 1 |
Chemistry: Philosophy for Physical Scientists
In progress
Science is a strikingly successful and powerful feature of contemporary human cultures: it has transformed lives, enabled great technological feats and often revealed the world to be a much stranger place than appearances suggest. But what is science, really, and how and why has it been so successful? |
| Tue 7 |
This is a practical skills-based course which comprises of 1 optional drop-in session and 6 compulsory instructor-lead statistics sessions. These will take place in Todd Hamied |
| Wed 8 |
PhD research journey can present many challenges in our ability to maintain work life balance and work sustainably while progressing towards our goals. Addressing the challenges of work-life balance and sustainability in the context of a PhD is crucial for the well-being and effectiveness of researchers. This interactive session aims to create a space for researchers to hack key issues for developing sustainable academic practices and offers a toolkit of reliable, evidence-based strategies for wellbeing management |
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Chemistry: Philosophy for Physical Scientists
In progress
Science is a strikingly successful and powerful feature of contemporary human cultures: it has transformed lives, enabled great technological feats and often revealed the world to be a much stranger place than appearances suggest. But what is science, really, and how and why has it been so successful? |