Incubator Summer Academy - From Zero to Hero

Sep 12, 2022, 9:00 AM → Sep 23, 2022, 11:59 PM Europe/Berlin

HIDA Courses , HIFIS Noreply Bot (Functional Account)

The five Helmholtz incubator platforms Helmholtz AI, Helmholtz Imaging, HIFIS, HIDA and HMC have teamed up to create an exciting program:

• Data science workshops from beginner to expert level,
• a data challenge,
• lectures,
• plenty of networking opportunities

From fundamental workshops like „Introduction to Python“ to advanced courses on „Machine Learning for Instance Segmentation and Tracking“, participants will be able to pick and choose offers that best suit their experience levels and interests. In our data challenge, you and your teammates can put your (newly acquired) knowledge to the test. You’ll get the chance to network with colleagues from all Helmholtz centers and learn more about career opportunities and data science-related exchange programs. Finally, don’t miss our lectures by data science experts!

The Incubator Summer Academy - From Zero to Hero is open to all doctoral and postdoctoral researchers in the Helmholtz Association. Additionally, a small number of seats in our workshops are reserved for Master students, doctoral and postdoctoral students from other research institutions and universities.

How to register

The registration deadline is August 29, 2022. Entering in the data challenge will be possible until September 22, 2022.

1. Log in to indico first at https://events.hifis.net
2. Have a look at the program below. Choose the workshop(s) you would like to attend keeping in mind that some workshops require certain previous experience/knowledge and you should not pick two courses that overlap timewise.
3. If you want to register for a workshop, click on the link "→ Register here ←" in the workshop description. Alternatively, you can click on the respective "Apply for registration" or "Register" button in the list of registration forms at the bottom of this general information page.
4. You will be directed to the registration form for that workshop. Fill it in and click on "Apply".
5. You will receive a registration notice via e-mail. Please note that this is not yet a confirmation.
6. Please make your own calendar entries so that you do not miss the workshops you registered for.
7. If you are selected as a participant for the workshop, you will be notified about a week prior to the Incubator Summer Academy.

For certain events, you will be directed to external registration pages.

Please note that all workshops will take place online and attendance is free of charge.

 

Gather.town

In our gather.town space you will be able to meet and mingle with other attendees of the Incubator Summer Academy. You'll be able to find out more about our platforms and career opportunities at Helmholtz and beyond. Have a virtual drink at our bar during one of the daily dedicated time slots for networking and get to know like-minded people from other Helmholtz centers!

For the teams competing in our data challenge, there will be rooms in our gather.town space where you can meet and discuss your progress.

The link to our space will be published at a later point.

Questions?

Write us at hida-courses@helmholtz.de

Monday, September 12

9:00 AM → 10:00 AM General

9:00 AM Opening Session and Keynote Speech

Join us in the opening of the Incubator Summer Academy!

This event will be take place via Zoom.

→ Register here ←

Speakers: Andreas Kosmider (Helmholtz Association) , Fabian Theis (Helmholtz AI) , Otmar D. Wiestler (Helmholtz Association)

Präsentation_Fabian_Theis_ML in cells.pdf

10:00 AM → 6:00 PM Workshops (HIFIS)

10:00 AM Fundamental: Introduction to Python

Note: Due to huge demand we will offer this event also on 6., 9. and 12. September. Please choose the date that best suits you when registering.

In this workshop, participants will learn how to work with the Python programming language. We will introduce the basic building blocks needed to "make the computer do stuff" and lay a solid basis for future self-guided learning or more advanced courses.

No prior knowledge in programming is required. We do recommend Thonny (https://thonny.org/) as a good starter tool, but you are free to bring your own setup.

We will include a break of 30 minutes after around 90 minutes of workshop and a lunch break of 60 minutes.

→ Register here ←

Speaker: Fredo Erxleben (Helmholtz-Zentrum Dresden-Rossendorf)

Tuesday, September 13

9:00 AM → 3:00 PM Workshops (HIFIS)

9:00 AM Fundamental: Introduction to Git

The workshop provides a solid introduction into the practical usage of the version control system Git in combination with the collaboration platform GitLab.

This workshop will cover the following topics:

• Introduction to version control
• Git setup
• Basic local Git workflow
• Branching and merging
• Resolving Conflicts

→ Register here ←

Speakers: Benjamin Wolff (Deutsches Zentrum für Luft- und Raumfahrt) , Tobias Schlauch (DLR)

10:00 AM → 12:00 PM Workshops (Helmholtz Imaging)

10:00 AM Intermediate: Sharing Scientific Software Solutions Across Tools and Domains with Helmholtz Imaging Solutions

Brief content:
1. Simplifying reproducibility for users and authors of scientific tools
2. Introduction to Helmholtz Imaging Solutions and Album
3. Basics of using Helmholtz Imaging Solutions
4. Writing your own Helmholtz Imaging Solution
5. Publishing solutions in a catalog

→ Register here ←

Speakers: Deborah Schmidt , Helmholtz Imaging

1:00 PM → 6:00 PM Workshops (Helmholtz AI)

1:00 PM Fundamental: Reproducible Data Science / day 1

Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses

This course will span over two days. The second half will be on September 14 at 2 pm.

→ Register here ←

Speaker: Heidi Seibold

Wednesday, September 14

9:00 AM → 3:00 PM Workshops (HIFIS)

9:00 AM Fundamental: Introduction to GitLab

This workshop provides a practical introduction into GitLab.

In detail, we cover the following topics:
- Overview about GitLab
- Working with the Git repository
- Planning tasks using Issues
- Collaboration using Merge Requests
- Overview of advanced functionalities

→ Register here ←

Speakers: Benjamin Wolff (Deutsches Zentrum für Luft- und Raumfahrt) , Tobias Schlauch (DLR)

9:00 AM Intermediate: Data Science with Python (Pandas)

In this quick workshop we will get an overview over the data science framework pandas.

Participants should have some fundamental knowledge on how to work with Python and have a working Python-installation ready and the pandas-package installed.

The workshop contains a code-along introduction and a introduces a set of exercises to build some practical experience.
Instructors will be available to help with the exercises and give feedback on your solutions.

The workshop includes a 30-minute break every 90 minutes and offers the opportunity to take a lunch break at your own discretion during the exercise part (after 12:30).

→ Register here ←

Speakers: Fredo Erxleben (Helmholtz-Zentrum Dresden-Rossendorf) , Thomas Foerster (HZDR)

9:00 AM → 2:00 PM Workshops (HMC)

9:00 AM Fundamental: Fundamentals of Scientific Metadata / day 1

In this course we will look at the intricate relationship between (digital) research data, metadata and knowledge, discuss why metadata is critical in today’s research, as well as explain some of the technologies and concepts related to structured machine-readable metadata.

Have you ever struggled to make sense of scientific data provided by a collaborator - or even understanding your own data 5 months after publication? Do you see difficulties in meeting the data description requirements of your funding agency? Do you want your data to have lasting value, but don’t know how to ensure that?

Precise and structured description of research data is key for scientific exchange and progress - and also for the recognition of your effort in data collection. The solution: make your data findable, accessible, interoperable and reusable by describing them with metadata.

You will learn:

• about the differences between and the importance of data & metadata
• to annotate your research data with structured metadata
• to find and evaluate a suitable metadata framework and data repository
• to use basic Markdown / JSON / XML
• which tools are already available to level up your metadata annotation game
• why structured metadata is important and how it can increase your scientific visibility

organized by HMC Hub Information

→ Register here ←

Speakers: Annika Strupp , Silke Gerlich (HMC)

2:00 PM → 5:00 PM Workshops (Helmholtz AI)

2:00 PM Fundamental: Reproducible Data Science / day 2

Topics:
- What is reproducible research?
- Reproducible research practices
- Project organisation for reproducible research
- Reproducible analyses

This is day two of the course starting on September 13 at 1 pm.

Speaker: Heidi Seibold

5:00 PM → 6:00 PM Data Challenge

5:00 PM Data Challenge: Kick-off

Help a hematologist out!

Join us and find elegant domain transfer solutions for blood-cell classification.

Manual classification of blood cells is a tedious, but important task, for instance to diagnose diseases such as anemia or leukemia. Machine learning makes it easier, but algorithms that work on one set of images might not work on another. Join this challenge and find a solution that may contribute to making clinicians lives easier.

We’ll kick off on September 14 with an introduction to the challenge and end with our award ceremony on September 23. You’ll be working on your own time. On all days of the challenge there will be mentor support availabe in gather.town from 12-13 pm. Computing resources are available via HAICORE.

Sign up now!

Deadline for submissions: 22.09.2022

→ Register here ←

environment.yml

Helmholtz Challenges Platform

starter_notebook.ipynb

Kick-off presentations DC_Kickoff_Presentation.pdf Gruber_Datasets.pdf

7:00 PM → 10:00 PM General

Thursday, September 15

9:00 AM → 2:00 PM Workshops (HIFIS)

9:00 AM Intermediate: Introduction to GitLab CI

This workshop provides a practical introduction to Continuous Integration (CI) using GitLab CI. It will cover these aspects:

• Setting up a basic CI pipeline with linting and testing.
• Advanced concepts to optimize the CI implementation. With a focus on
  • Performance
  • Reducing Redundancies
  • Concise pipeline definition and cross-project reuse.
• Optional: Other useful examples what CI could be used for.

→ Register here ←

Speakers: Christian Hueser (Helmholtz-Zentrum Dresden-Rossendorf (HZDR)) , Norman Ziegner (UFZ) , Tobias Huste (Helmholtz-Zentrum Dresden-Rossendorf)

9:00 AM Intermediate: Visualization with Python (matplotlib)

In this quick workshop we will get an overview over the data visualization framework matplotlib.

Participants should have some fundamental knowledge on how to work with Python + pandas and have a working Python-installation ready and the pandas and matplotlib-packages installed.

The workshop contains a code-along introduction and a introduces a set of exercises to build some practical experience.
Instructors will be available to help with the exercises and give feedback on your solutions.

The workshop includes a 30-minute break every 90 minutes and offers the opportunity to take a lunch break at your own discretion during the exercise part (after 12:30).

→ Register here ←

Speakers: Fredo Erxleben (Helmholtz-Zentrum Dresden-Rossendorf) , Thomas Foerster (HZDR)

9:00 AM → 2:00 PM Workshops (HMC)

9:00 AM Fundamental: Fundamentals of Scientific Metadata / day 2

In this course we will look at the intricate relationship between (digital) research data, metadata and knowledge, discuss why metadata is critical in today’s research, as well as explain some of the technologies and concepts related to structured machine-readable metadata.

Have you ever struggled to make sense of scientific data provided by a collaborator - or even understanding your own data 5 months after publication? Do you see difficulties in meeting the data description requirements of your funding agency? Do you want your data to have lasting value, but don’t know how to ensure that?

Precise and structured description of research data is key for scientific exchange and progress - and also for the recognition of your effort in data collection. The solution: make your data findable, accessible, interoperable and reusable by describing them with metadata.

You will learn:

• about the differences between and the importance of data & metadata
• to annotate your research data with structured metadata
• to find and evaluate a suitable metadata framework and data repository
• to use basic Markdown / JSON / XML
• which tools are already available to level up your metadata annotation game
• why structured metadata is important and how it can increase your scientific visibility

organized by HMC Hub Information

This is day two of the course starting on September 14 at 9 am.

Speakers: Annika Strupp , Silke Gerlich (HMC)

2:00 PM → 6:00 PM Workshops (Helmholtz AI)

2:00 PM Intermediate: Introduction to Machine Learning / day 1

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)

More information can be found here: https://deeplearning540.github.io/

→ Register here ←

Speaker: Peter Steinbach (HZDR)

intro slides (pdf)

learnerpack

shared notes

2:00 PM → 5:30 PM Workshops (Helmholtz Imaging)

2:00 PM Intermediate: Machine Learning-Based Biomedical Image Analysis

Brief Content:
1. Introduction to Machine Learning-based Image Analysis
2. Applications and Examples on Biomedical Images
3. Introduction to nnU-Net
4. Hands-on Tutorial on how to train and apply nnU-Net (using google colab). The tutorial starts right after this course and will take 45min, number of participants is limited to 30.

→ Register here ←

Speakers: Carsten Lüth (Helmholtz Imaging) , Helmholtz Imaging , Lukas Klein (Helmholtz Imaging) , Paul Jäger (Helmholtz Imaging)

4:45 PM Intermediate: Tutorial for "Machine Learning-Based Biomedical Image Analysis"

Brief Content:
This tutorial is designed as a follow-up to the intermediate course "Machine Learning-Based Biomedical Image Analysis" on September 15, 2022 at 10:00 by Paul Jäger et al.

It comprises a hands-on Tutorial on how to train and apply nnU-Net (using google colab). The number of participants is limited to 30.

Participation in the course "Machine Learning-Based Biomedical Image Analysis" is mandatory.

Speakers: Carsten Lüth (Helmholtz Imaging) , Helmholtz Imaging , Lukas Klein (Helmholtz Imaging) , Paul Jäger (Helmholtz Imaging)

Friday, September 16

9:00 AM → 5:00 PM Workshops (Helmholtz AI)

9:00 AM Intermediate: Introduction to Machine Learning / day 2

This is day two of the course starting on September 15 at 2 pm.

This course will introduce participants to the concepts of AI and Machine Learning, covering clustering and clasifications fundamentals as well as practical experience with standard methods for both techniques. Lastly, participants will gain an insight on best practises for evaluating a machine learning model's performance (ROC curve, FPR etc.)

More information can be found here: https://deeplearning540.github.io/

Speaker: Peter Steinbach (HZDR)

shared notes

10:00 AM → 12:00 PM General

10:00 AM HIDA lecture: Data-Driven Inertial Sensing

The purpose of navigation is to determine the position, velocity, and orientation of manned and autonomous platforms, humans, and animals. Obtaining accurate navigation commonly requires fusion between several sensors, such as inertial sensors and global navigation satellite systems, in a model-based nonlinear estimation framework. Recently, data-driven approaches applied in various fields show state-of-the-art performance, compared to model-based methods. In this talk, we address data-driven based navigation algorithms, recently derived at the autonomous navigation and sensor fusion lab. The purpose of those algorithms is to enhance common navigation and estimation tasks and open new possibilities for accurate and robust navigation. Data driven inertial navigation topics included in this talk will highlight hybrid learning and end to end learning approaches for different platforms and applications such as: pedestrian dead reckoning with inertial sensors, quadrotor dead recooking, learning vehicle trajectory uncertainty by hybrid models, and autonomous underwater vehicle navigation.

This lecture will take place in a hybrid format: We will stream the talk via Zoom from our HIDA offices in Berlin-Mitte.

→ Register here ←

Speaker: Itzik Klein (The Hatter Department of Marine Technology, Charney School of Marine Sciences, University of Haifa, Israel)

11:00 AM General: Helmholtz Imaging for you!

From Helmholtz Imaging Modalities to the Helpdesk to Solutions to great images! A quick tour through the Helmholtz Imaging portfolio and how you can exploit our support and services to do your imaging experiments.

→ Register here ←

If you want to join spontaneously, here is the link:
https://desy.zoom.us/j/66379738048 (Kenncode: HI4U)

Speakers: Helmholtz Imaging , Philipp Heuser (HIP/DESY)

Monday, September 19

9:00 AM → 5:00 PM Workshops (Helmholtz AI)

9:00 AM Intermediate: Introduction to Deep Learning / day 1

This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.

The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning can be somewhat intimidating.

We start with explaining the basic concepts of neural networks, and then go through the different steps of a Deep Learning workflow. Learners will learn how to prepare data for deep learning, how to implement a basic Deep Learning model in Python with Keras, how to monitor and troubleshoot the training process and how to implement different layer types such as convolutional layers.

More information can be found here: https://carpentries-incubator.github.io/deep-learning-intro/

→ Register here ←

Speaker: Peter Steinbach (HZDR)

20220919-zero-to-hero-intro2dl-Steinbach.pdf

learnerpack

shared notes

2:00 PM → 5:00 PM POSTPONED: Intermediate: Cooperation HMC + Helmholtz Imaging: Imaging Metadata

Metadata for scientific images is crucial for the success of any imaging experiment. What are metadata, where do you find them, how do you exploit them? The use of metadata in imaging highly depends on the domain. In some research areas metadata is already a well established standard while others scribble them in their notebook.

Here we will give an introduction to metadata in imaging, using some use cases as examples, and show you some hands on examples how to deal with them in python.

Agenda:

• What is metadata?
• Imaging Modalities in the case studies
• Case Study - Photon and Neutron Science Imaging
• Case Study - Oceanic Imaging
• Case Study - Medical Imaging
• Hands-on: Jupyter notebook for image metadata

Basic Python knowledge will help you to follow the hands-on (but it is not mandatory).
If you want to learn more about metadata, we invite you to take a look at HMCs training material collection: https://helmholtz-metadaten.de/en/hmc-office/training-material-collection

→ Register here ←

Speakers: Luigia Cristiano (HZB) , Marco Nolden (DKFZ) , Philipp Heuser (HIP/DESY) , Timm Schoening (GEOMAR)

Tuesday, September 20

9:00 AM → 5:00 PM Workshops (Helmholtz AI)

9:00 AM Intermediate: Introduction to Deep Learning / day 2

This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.

The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning can be somewhat intimidating.

We start with explaining the basic concepts of neural networks, and then go through the different steps of a Deep Learning workflow. Learners will learn how to prepare data for deep learning, how to implement a basic Deep Learning model in Python with Keras, how to monitor and troubleshoot the training process and how to implement different layer types such as convolutional layers.

More information can be found here: https://carpentries-incubator.github.io/deep-learning-intro/

This is day two of the course starting on September 19 at 9 am.

Speaker: Peter Steinbach (HZDR)

shared notes

3:00 PM → 5:00 PM General

3:00 PM Helmholtz Entrepreneurs: From Idea to I did

What is entrepreneurial thinking and why does it matter?

Entrepreurial thinking is a way of thinking and refers to the capacity to act upon opportunities and ideas, and to transform them into value for others. It is founded upon creativity, critical thinking and problem solving, taking initiative and perseverance and the ability to work collaboratively in order to plan and manage projects that are of cultural, social or financial value.

Why does it matter? Businesses and employers across all sectors presuppose the academic and technical excellence of graduates. However, they must increasingly differentiate and identify future employees based on core competencies and skills, such as creative problem-solving, teamwork, understanding of risk and overall resilience. In many countries, however, academic institutions are very slow to adjust, partly because traditional career advancement in academia is mostly dependent on research activity. In the same way as labour markets and workplaces are undergoing rapid change, higher education and research institutions need to adjust in order to stay relevant. This requires entrepreneurial thinking among students, researchers and staff alike.

This workshop is based on experiential and action-based learning and will give participants a short, hands-on introduction on what it means to think entrepreneurially and how it may be useful in career development.

→ Register here ←

Speakers: Emma van Holthe (Helmholtz AI) , Julian Alexandrakis (Helmholtz Transfer) , Mathieu Seyfrid (Helmholtz AI)

Wednesday, September 21

9:00 AM → 10:00 AM General

9:00 AM HIDA lecture: What is Health? Taking a Non Dualist Multi-Scale Approach to Studying Adaptive Immune Interactions

The reductive approach which sees health as the rejection of the other - be it cancer or pathogens is false. As we learn more about the individual characteristics of cells in the body and the variable forms of immune responses it becomes ever clearer that we need a new paradigm of study one that considers open systems of interactions across scales of biology rather than defining sharp borders of good and bad health outcomes. The immune system is comprised of multivariate B cells and T cells. To develop these repertiores they must first be tested for some level of activity. They are then activated during an immune response. Most commonly this secondary activation is seen to be by pathogens. However, it is becoming every clearer that these are not the only events that interest or influence are immune repertiores and their role in promoting health. The immune system also helps to cultivate and moderate the commensal bacteria in our gut and is a key factor in the modulation of cancer and autoimmunity. Setting goals and borders for the immune system is thus not an effective way to understand what it is doing. Instead we should study as far as we can the processes of immune interaction and change. In this lecture I will present our attempts to charecterize how the genome of B cell receptors encodes the potential for change in the adaptive immune system and how this is translated into actual patterns of diversity, implemented in a specific immune responses. I hope these ideas and findings will lead to further questions and help spark new conversations and research projects.

This lecture will take place via Zoom.

→ Register here ←

Speaker: Prof. Uri Hershberg (Chair of the Center for Biophysics and Quantitative Biology, University of Haifa, Israel)

9:00 AM → 3:00 PM Workshops (HIFIS)

9:00 AM Intermediate: Foundations of Research Software Publication

We will provide you with actionable advice about how to prepare your research code before publishing it or submitting it alongside a research publication.

This workshop will cover the the following topics:

• Code repository structuring
• Minimum coding practices
• Documentation
• Open source licensing
• Minimum software release practices
• Software citation

We demonstrate the practical implementations of the presented topics using a data publication project as an example.

→ Register here ←

Speakers: Benjamin Wolff (Deutsches Zentrum für Luft- und Raumfahrt) , Tobias Schlauch (DLR)

1:00 PM → 3:00 PM Workshops (Helmholtz Imaging)

1:00 PM Advanced: Machine Learning for Instance Segmentation and Tracking

based on python, follow-up to the course by Paul Jäger on September 15, 2022.

The course will build on the introduction to convolutional neural networks in Imaging by Paul Jäger, and will cover essential rules for designing your own networks, in particular when dealing with large image data. You will get hands-on experience in setting up and training your own networks for image analysis tasks like images classification and image segmentation.

The number of participants is limited to 20.

→ Register here ←

Speakers: Dagmar Kainmüller (MDC Berlin) , Helmholtz Imaging

2:00 PM → 5:30 PM Workshops (Helmholtz AI)

2:00 PM Intermediate: Introduction to Statistical Learning / day 1

Topics covered involve basic concepts in statistical learning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).

→ Register here ←

Speaker: Tingying Peng

Thursday, September 22

9:00 AM → 6:00 PM Workshops (Helmholtz AI)

9:00 AM Intermediate: Introduction to Statistical Learning Day 2

Topics covered involve basic concepts in statistical searning, as well as supervised learning techniques (high-dimensional regression and classification) and unsupervised learning (mixture models and dimension reduction).

This is day two of the course starting on September 21 at 2 pm.

Speaker: Tingying Peng

2:00 PM Advanced: Introduction to Interpretable Machine Learning

During this course participants will get an introduction to the topic of Explainable AI (XAI). The goal of the course is to help participants understand how XAI methods can help uncover biases in the data or provide interesting insights. After a general introduction to XAI, the course goes deeper into state-of-the-art model agnostic interpretation techniques as well as a practical session covering these techniques. Finally, we will focus on two model specific post-hoc interpretation methods, with hands-on training covering interpretation of random forests and neural networks with imaging data to learn about strengths and weaknesses of these standard methods used in the field.

→ Register here ←

Speakers: Christina Bukas (Helmholtz AI) , Donatella Cea (Helmholtz AI) , Elisabeth Georgii (Helmholtz AI) , Erinc Merdivan (Helmholtz AI) , Harshavardhan Subramanian (Helmholtz AI) , Helena Pelin (Helmholtz AI) , Helene Hoffmann (Helmholtz AI) , Isra Mekki (Helmholtz AI) , Lisa Barros de Andrade e Sousa (Helmholtz AI) , Mahyar Valizadeh (Helmholtz AI) , Marie Piraud (H.AI/ HMGU) , Rao Muhammad Umer (Helmholtz Munich) , Sebastian Starke (Helmholtz AI)

requirements.txt

9:00 AM → 2:00 PM Workshops (Helmholtz Imaging)

9:30 AM Optional: Solve installation issues (related to the Napari Workshop)

This 30min slot is optional for those who had problems installing the program.
https://www.napari-hub.org/plugins/devbio-napari#installation

Please do install the programm before!
In case of issues with the installation, attendees can reach out any time – before the course - by opening a thread on https://image.sc and tagging @haesleinhuepf .

Use this session to solve still remaining issues with Robert (@haesleinhuepf).

Speakers: Helmholtz Imaging , Robert Haase (TU Dresden)

10:00 AM Intermediate: Introduction to Napari

It is recommended to take a Python-Basics Course before. For example from the first week of this Summer Academy.

In this course we will introduce image processing with Python, Jupyter lab and Napari. Students will learn how to process images interactively in Napari and afterwards how to replicate the same results in Jupyter notebooks. Additionally, the students will get an idea how to export tables of measurements and plot results in Jupyter notebooks. The notebooks can then be conserved and allow reproducible image data science mid-/long-term. We will use Python libraries such as numpy, scipy, scikit-image, pandas and matplotlib. Furthermore, GPU-accelerated image processing using pyclesperanto for processing 3D data will be introduced as well.

Attendees who attend the course should go through the installation instructions provided on this website:
https://www.napari-hub.org/plugins/devbio-napari#installation

In case of issues with the installation, attendees can reach out any time – before the course - by opening a thread on https://image.sc and tagging @haesleinhuepf . Or consider joining the session at 9:30 to solve installation issues.

This course is an excelent follow up to the lecture series Imaging - from Organisms to Molecules runing this summer term. Participants of the lecture will be given preference in participation.

→ Register here ←

Speakers: Helmholtz Imaging , Robert Haase (TU Dresden)

4:00 PM → 6:00 PM General

4:00 PM General: Helmholtz Career Corner

Come and join us in the Helmholtz Career Corner in gather.town!

This is the place where you can gather information about career opportunities within the Helmholtz Community- be it the latest job openings or exchange opportunities. Get an overview of the activities of some Helmholtz Centers and platforms, and network with your peers and representatives from the Helmholtz Community.

Additionally, we are happy to announce the addition of two new partners to the Career Corner: Siemens and ELLIS will present their PhD and Postdoc programs.

You have already received the link to our gather.town space by email at the beginning of the Incubator Summer Academy. We are looking forward to seeing you there!

→ Register here ←

Speakers: Sophia Buehrig , Stephanie Schworm , Viktoria Schwarze (Helmholtz Information & Data Science Academy)

2022-09_IncubatorSummerSchool_HMC_Overview_v1.2.pdf

HDS-LEE kompakt.pdf

HelmholtzAI_General_Poster1.pdf

Helmholtz-Imaging.pdf

Helmholz-Incubator-Folder_2022 (2).pdf

HIDA summer academy 2022_MUDS Poster.pdf

HIFIS_overview_2022_03_en.pdf

Poster_HIDA.pdf

Presenting DASHH_Poster-1.pdf

Friday, September 23

10:00 AM → 11:00 AM General

10:00 AM HMC FAIR Friday: Metadata as a key? Open science, good scientific practice and research integrity

Openness is a pillar for good scientific practice and contributes to research integrity. How do metadata fit in here?

About HMC FAIR Friday
To stimulate and support interdisciplinary exchange on FAIR and (meta)data, the Helmholtz Metadata Collaboration (HMC) - in close cooperation with the Helmholtz Information & Data Science Academy (HIDA) - is organising the lecture series.

Roland Bertelmann will kick off our fall/winter edition 2022.

→ Register here ←

Speaker: Roland Bertelmann (Helmholtz Open Science Office)

11:00 AM → 12:00 PM Data Challenge

11:00 AM Data Challenge: Closing & Award Ceremony

The top three teams will present their solutions to the Incubator Summer Academy data challenge "Help a hematologist out!".

The closing & award ceremony will take place via Zoom.

Register here