Seminars take place daily, and are open to everyone. The seminars fall into different categories, designated by different colors, summarised below.
One seminar (previously Pink seminars): Group leaders (Weds at 13:00)
Seminars given by group leaders from across the different EMBL stations. Group leader seminars give an excellent overview of the exciting research that happens at EMBL.
White seminars: Internal seminars (Mon, Tue, Thu & Fri at 13:00/13:15)
Unit Seminars take are the most regular type of white seminar. The seminars presented by members of your unit are likely to be particularly relevant to your research/interests, but you are welcome to attend any that interest you.
- Monday - Genome Biology Unit
- Tuesday - Development Biology Unit
- Thursday - Cell Biology & Biophysics Unit
- Friday - Structural and Computational Biology Unit
Blue seminars: External speakers
Seminars given by people from outside EMBL - invited/visiting scientists, industry professionals, core facility representatives, etc.
Green Seminar: Distinguished Visitor Lectures
The EMBL Distinguished Lecture is a seminar series where eminent scientists in biology are invited by the whole of the Heidelberg lab to give a seminar of broad interest at EMBL. The lecture will be streamed live to all EMBL sites.
Yellow seminar: Science and society seminar
Yellow seminars are rare, they always connect science and society, often as part of conferences or special events. They often provide a different perspective on our research, connecting EMBL with the wider world.
Bio-IT organises a lot of events aimed at computational scientists at EMBL. These can be useful opportunities to get to know other members of the community, from across the different units and groups, and to learn new skills, approaches, and perspectives for computational research.
Learning tom program is like learning a language - you need to practice regularly to improve/retain your knowledge! The EMBL Coding Club meets weekly, providing an informal environment to practice and improve your programming/computing skills, and to get to know other people interested in doing the same. To find out more about the club, and browse our list of recommended learning resources, check out the clubs homepage on the Bio-IT portal: bio-it.embl.de/coding-club.
Training courses, taught by Bio-IT community members, run regularly throughout the year. These courses are usually free to attend, and cover a range of different computing skills, including (but not limited to) programming and command line computing, scientific data management, and software version control. You can find out more, and register for upcoming events, on the Bio-IT Portal.
Note that places on these courses tend to fill up very quickly, and the best way to ensure that you find out about events before it's too late is by signing up to the firstname.lastname@example.org mailing list. You can subscribe at bio-it.embl.de/mailing-list-sign-up/.
Bio-IT Taskforce Meetings
Every two months, the Bio-IT Taskforce brings together scientists and computational support staff from across the units, to discuss issues and strategy affecting the computational biology community at EMBL HD. Membership is voluntary and we are always keen to welcome new members. If you are interested in joining, please contact email@example.com.
Bio-IT provides advice and consulting on general computational biology tasks, command line/scripting jobs, and biocomputing at EMBL Heidelberg in general. You can contact them any time on firstname.lastname@example.org, or come to one of the weekly drop-in sessions. Sessions take place 10-12 on Tuesday mornings in the cafeteria.
Bio-IT Beer Sessions
Usually taking place on the second Wednesday of each month, Bio-IT beer sessions provide an opportunity to get to know other members of the computational biology community better. Each session is based around an informal discussion of a technical theme of general interest. Recent examples include best usage of the collaborative features of GitLab and a comparison of workflow management systems for bioinformatic analysis pipelines.