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Young Statisticians Lecture Series -

Modern Statistical Methods for Life Sciences

This is a recurring online event organized by the Early Career Working Group (AG Nachwuchs) of the German Region of the International Biometric Society (IBS-DR).

With this lecture series, we would like to give students of statistics and biometry the opportunity to present their Master’s thesis or current PhD project in a larger and more flexible time frame than is usual at conferences.

Visit our homepage or follow us on Twitter @AGNachwuchs_IBS to stay updated on our events and more.

General information

Format:

Lectures take place live via Zoom and include a presentation of 20 to 40 minutes followed by a Q&A.

Participation:

Everyone interested is welcome to attend the lectures. To receive the Zoom invitations, simply register for our lecture series below.

Apply for a talk:

We would like to encourage Young Statisticians to not only participate as an attendee but also to present their work in one of our upcoming lectures. If you would like to give a talk during this lecture series, please send your abstract to:

[email protected]

Upcoming lectures

Julian Rodemann

Department of Statistics, LMU Munich

TOPIC: "Learning Under Weak Supervision: Some Insights From Decision Theory"

DATE: April 18, 2023, at 4 PM (CEST)

Registration

First name

Last name

Email address

Organization

So that we know where our flyers were distributed.

Position

e.g. Bachelor's/Master's/PhD student; Postdoc; Universtity staff; Researcher; Other

Register for the Young Statisticians Lecture Series to get informed about all upcoming lectures (including the Zoom links).

You will receive Zoom invitations, a reminder one day before a lecture, and further important information like schedule changes. We'll send you emails related to this lecture series only. You may unsubscribe at any time using the link in our emails.

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You may unsubscribe at any time using the link in our emails. Your personal data will only be used for sending you emails related to this lecture series. Your data will not be shared with any third parties.

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