Department of Chemistry course timetable
Tuesday 24 November 2020
| 10:00 |
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. This compulsory training will available online via moodle. We are offering drop in sessions for you to discuss queries with the course trainer. Please book one 15 minute session. You will be asked to confirm your attendance one day before, if you do not confirm your slot will be allocated to someone else. |
| 10:15 |
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. This compulsory training will available online via moodle. We are offering drop in sessions for you to discuss queries with the course trainer. Please book one 15 minute session. You will be asked to confirm your attendance one day before, if you do not confirm your slot will be allocated to someone else. |
| 10:30 |
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. This compulsory training will available online via moodle. We are offering drop in sessions for you to discuss queries with the course trainer. Please book one 15 minute session. You will be asked to confirm your attendance one day before, if you do not confirm your slot will be allocated to someone else. |
| 10:45 |
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. This compulsory training will available online via moodle. We are offering drop in sessions for you to discuss queries with the course trainer. Please book one 15 minute session. You will be asked to confirm your attendance one day before, if you do not confirm your slot will be allocated to someone else. |
| 14:00 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
| 14:15 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
| 14:30 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
| 14:45 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
| 15:00 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
| 15:15 |
Chemistry: Fortran 90/95 Drop in Q&A
Finished
An opportunity ask questions to the course trainer re Fortran 90/95.
|
Wednesday 25 November 2020
| 10:00 |
Communicating your research in an engaging and easily understood manner is important for any audience and all the more so for non-academic audiences. This workshop will take you through the art and science of engaging communication, and outline the opportunities and support within the University for public engagement. |
Monday 11 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Wednesday 13 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Monday 18 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Wednesday 20 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Monday 25 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Tuesday 26 January 2021
| 14:00 |
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. |
Wednesday 27 January 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Thursday 28 January 2021
| 14:00 |
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. |
Friday 29 January 2021
| 14:00 |
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. |
Monday 1 February 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Tuesday 2 February 2021
| 14:00 |
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. |
Wednesday 3 February 2021
| 10:00 |
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. Once you book this course, you will need to register for each session via Zoom. |
Thursday 4 February 2021
| 14:00 |
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. |
Friday 5 February 2021
| 14:00 |
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. |