All Department of Chemistry courses

There are 8 sessions in total DD1 to DD8 starting from 18th May and ending 10th June. The sessions are listed below:

DD1: Introduction to Drug Discovery and path to clinic Bobby Glen (UoC) 18th May, 10:00 - 12:00

SESSION CANCELLED DD2: Pharmacology + Biochemical and Biophysical methods Chris Stubbs (AZ) 20th May, 10:00 - 12:00

DD3: Structural Biology Gavin Collie (AZ) 25th May, 10:00 - 12:00

DD4: Hit generation methods and tactics Ben Whitehurst (AZ) 27th May, 10:00 - 12:00

DD5: Potency & thermodynamics Steve Atkinson (AZ) 1st June, 10:00 - 12:00

DD6: Computational methods (Session 1) - Modelling/MD/potency prediction/ML/AI Kathryn Giblin (AZ) 3th June, 10:00 - 12:00

DD7: Computational methods (Session 2) - Modelling/MD/potency prediction/ML/AI Bobby Glen (UoC) 8th June, 10:00 - 12:00

DD8: Impact of structures and physchem on DMPK/safety Jen Nelson (AZ) 10th June, 10:00 - 12:00

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.

Join Cambridge Careers Consultant, Raj Sidhu for a discursive and interactive session where you will learn:

• What career options are open to you after a Chemistry PhD or PostDoc
• What alumni of the Department of Chemistry are doing now
• How to structure and approach career-thinking, during your PhD or PostDoc

All questions will be warmly welcomed throughout.

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!

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.

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.

'Enhance focus, reduce stress, use time more wisely and be more productive.

Learn to:

• Establish a method that works for you to enhance focus for the most important work (Deep Work)
• Reduce distraction and prioritise more effectively
• Establish 1 daily high quality mini break, to relieve stress, reduce self criticism and strengthen resilience
• Create the space to recognise your achievements each day - increase self awareness and confidence
• Combining proven neuroscience & mindfulness based techniques into useful daily habits.

In these sessions, Dr. Mukund S. Chorghade will discuss the pivotal role played by Process Chemistry / Route Selection in the progress of a chemical entity from conception to commercialization.

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These lectures will provide an introduction to the field with relevant background and theory, a survey of main strategies that have been used and are most widely practised and finally will cover current challenges and latest approaches in the area.

In this course we will give a brief introduction to the theory and simulation of molecules and materials. The focus will be on explaining at an introductory level the types of problems and properties that can be tackled with current techniques in theoretical chemistry. Limitations of current methods and future perspectives of where the field is heading and its intersection with modern experimental methods will also be discussed.

In these introductory lectures, you will learn how machine learning inspired methods have been making inroads into molecular modelling, particularly first principles modelling. The focus will be on descriptors and representations of atomic geometry and modelling potential energy surfaces.

The course will be a brief overview of polymer chemistry, covering a range of synthetic methods and interests in the context of drug delivery.

These lectures seek to provide an overarching vision of chemical synthesis methodology using machinery as enabling tools. They will highlight current capabilities and limitations in this highly digitally connected world and suggest where new opportunities may arise in the future, going well beyond our present levels of innovation and automation.

In order to use machine learning methods on molecular data, it is necessary to express molecular structures in a form which can be used as the input. This workshop will outline ways in which this challenge has been addressed, including the InChI, SMILES, fingerprints and other ways of expressing molecules as text strings. The strengths and weaknesses of the various approaches makes them suitable for different applications. What will be most appropriate for the molecular problems you are tackling?

Course provider: Timur Madzhidov

Course description: This is an advanced workshop providing a hands-on opportunity to work on several case studies in teams during the workshop. Several applications of classical ML and deep learning approaches in chemistry will be reviewed. As part of the tasks assigned to groups, the fundamentals such as data acquisition, preparation and modelling will be included.

This complimentary hands-on workshop is offered to PhD students and researchers at University of Cambridge who want to learn more about design of experiments (DOE) and data analysis. DOE skills are highly demanded by industry and still under-represented in many university curricula. Design of experiments is a practical and ubiquitous approach for exploring multifactor opportunity spaces, and JMP offers world-class capabilities for design and analysis in a form you can easily use without any programming. To properly uncover how inputs (factors) jointly affect the outputs (responses), DOE is the most efficient and effective way – and the only predictable way – of learning. Unlike the analysis of existing data, designed experiments can tell you about cause and effect, drive innovation and test opportunities by exploring new factor spaces. In addition to classical DOE designs, JMP also offers an innovative custom design capability that tailors your design to answer specific questions without wasting precious resources. Once the data has been collected, JMP streamlines the analysis and model building so you can easily see the pattern of response, identify active factors and optimize responses.

In this course you will learn to understand why to consider DOE analyze experiments with a single categorical factor using analysis of variance (ANOVA) analyze experiments with a single continuous factor using regression analysis understand the difference between classical and optimal designs design, analyze and interpret screening experiments incl. Definitive Screening Design design, analyze and interpret experiments in response surface methodology augment designs for sequential experimentation apply robust optimization evaluate and compare designs understand advanced features like blocking, split-plot experiments and covariates

The format of this course will be a mix of concept presentations, live demos and hands-on exercises. Most examples are inspired by chemistry and biotech, but can be easily transferred to other fields like materials science, agri-food science or engineering. Attendees should have access to JMP Pro (pre-installed). JMP Pro 17 is available for all attendees from University of Cambridge for both Windows and Mac. No prior knowledge required. All content and demos will be shared with the participants.

The course will be delivered by Lucy Colwell

This course will be delivered in person or via Zoom.

You will be informed closer to the date

This course will focus on recent progress in the application of kernel-based methods, Random Forests and Deep Neural Networks to modelling in chemistry. The material will build on the content of the core Informatics course and introduce new descriptors, advanced modelling techniques and example applications drawn from the current literature. Lectures will be interactive, with students working through computational exercises during class sessions.

The course will be delivered by Lucy Colwell

This course will be delivered in person or via Zoom.

You will be informed closer to the date

An applied introduction to probabilistic modelling, machine learning and artificial intelligence-based approaches for students with little or no background in theory and modelling. The course will be taught through a series of case studies from the current literature in which modelling approaches have been applied to large datasets from chemistry and biochemistry. Data and code will be made available to students and discussed in class. Students will become familiar with python based tools that implement the models though practical sessions and group based assignments.

The course will be delivered by Lucy Colwell This course will be delivered in person or via Zoom. You will be informed closer to the date

This course will introduce students to the central question of how to encode molecules and molecular properties in a computational model. Building on the compulsory informatics course (see previous table entry), it will focus on reactivity parameterisation and prediction. The basics of DFT calculations will be introduced, together with how DFT can be used to model reactions (including flaws, assumptions, drawbacks etc). Lecture based format will be complemented by practical sessions in setting up different DFT-based calculations.

During this workshop students will learn the appropriate strategies on how to write a research manuscript in subject areas related to the SynTech CDT. Participants will learn about when they should think about working towards writing up a paper, factors to consider when identifying the right journal in specific scientific area and practical writing tips. Students will also learn about the submission process and how to assess the feedback from the reviewers.

This workshop will be held online.

You will receive a link to sign into the workshop a few days before the session starts.

During this workshop students will learn how to develop skills in presenting information for a grant proposal and to arrange different sections. Participants will also learn how to review and respond to the feedback of assessors and how to revise proposals for resubmission in the case of rejection. By the end of this workshop students will gain a full understanding of the criteria most funders use to determine whether grant proposals are funded.

This will be an online workshop.

You will be sent a link to sign in closer to the date.

This course will introduce the new generation of molecules, including novel peptides, oligonucleotides, hybrids, and molecular conjugates, that are enabling novel strategies to address challenging targets and biological processes. This workshop will review these next generation therapeutics, and will highlight progress in this area towards a range of novel drug candidates.

The University of Cambridge has a well-deserved reputation for spinning out high technology startups from its world-class science research and innovation programs. It is the home of startups on the leading edge of medical technology, biotech, semiconductors, and quantum computing, among many other scientific frontiers. Six lectures by Mukund S. Chorghade and James Skinner will take the aspiring entrepreneur through the strategic considerations for starting a company.

Are you a post-doc (or a PI) at Chemistry applying for grants? Do you need to write a Data Management Plan (DMP) as part of your grant application but don't know how? Are you a post-doc (or PI) who is just interested in learning about writing data management plans? If so, this session is for you.

You will increasingly be required to write a DMP as part of your grant applications, but it is also useful to write one whenever you begin a research project, to help you plan how to manage your data effectively from the start.

During this session you will learn everything you need to know about data management plans:

• What they are
• Why they are increasingly required as part of grant applications
• What to include in data management plans
• Tools to help writing data management plans
• See example data management plans

Refreshments will be provided (tea, coffee, and biscuits).