Are you interested in bringing artificial intelligence and data science to the forefront of health research? Three top-level institutions – the Karlsruhe Institute of Technology, the German Cancer Research Center and Heidelberg University – have joined forces to tackle this exciting area by providing a unique doctoral program. Send your application if you can see the potential in techniques such as deep learning in the health sector and if you are ready to shape the future of our well-being.
The aim of the Helmholtz Information & Data Science School for Health (HIDSS4Health) is to attract, promote and train the best young talents at the interface between data science and health-related applications. HIDSS4Health offers a structured doctoral training program embedded in a highly interdisciplinary research environment, bringing together experts from the data and life sciences. The scientific curriculum is complemented by training measures that provide doctoral researchers with the key qualifications expected from future leaders in science and industry.
Proposed Projects for 2020
Details about the projects for this year's selection round can be found in this document.
The Helmholtz Information & Data Science Academy
As domain scientists from all research fields need to be equipped with knowledge, methods and tools in the areas of Information & Data Science, a training and education initiative for researchers in the Helmholtz Association has been established. The Helmholtz Information & Data Science Academy (HIDA) will coordinate networking, education and training activities throughout the entire Helmholtz Association. It bundles the resources of all Information & Data Science Schools (HIDSS), including HIDSS4Health.
Data Science Groups
Life Science Groups
The Durstewitz group develops statistical machine learning methods at the mathematical and algorithmic levels, with a focus on nonlinear time series analysis, nonlinear dynamical systems, and generative recurrent neural networks. Our main application domains are functional neuroimaging and electrophysiological data, as well as smartphone-based ecological momentary assessments, in psychiatry and neurology.
Our research focuses on (a) pattern recognition in biological data, multi-omics analysis and data integration with special application to cancer genomics as well as (b) translational and personalized oncology, molecular tumor boards, biomarker development and data analysis for clinical trials.
The goal of the HIDSS4Health curriculum is that its doctoral researchers become experts in data science and in at least one health-related field. It will include the ability to communicate with experts from both sides and to transfer knowledge from data to life science and vice versa. All lectures, courses, retreats and summer schools are held in English.
All doctoral researchers will receive feedback from a Thesis Advisory Committee (TAC). This consists of an interdisciplinary team of at least three Principal Investigators (PI), including PIs with data science and life science backgrounds from different institutions. TAC meetings will discuss the progress of the doctoral research project, the publication concept, working plans, cooperation potential with other doctoral researchers, planning of the mobility phase, as well as the supervision quality and career perspectives of the doctoral researcher. Although each doctoral researcher will belong to the main supervisor’s group, we recommend an associate membership in the group of a second PI, including an official second affiliation, regular stays in this group (such as once a week or one week per month) and integration in lab meetings etc. We anticipate that this will foster closer integration between data and life science expertise and a deeper understanding of both aspects.
In general, the doctoral thesis degree will be awarded by the informatics faculty of KIT or Heidelberg University, depending on your main supervisor’s individual affiliation. Each doctoral researcher who successfully finishes all training modules and the doctoral thesis project will receive a certificate as “Data Scientist”, including a confirmation regarding specialization in the health-related application domain. This certificate is a joint activity of the Faculty for Informatics at KIT and the Faculty for Mathematics and Computer Science at Heidelberg University.
Lectures, Workshops, Seminars
All incoming doctoral researchers start with the interdisciplinary course “Data Science & Health”. This is held by the PIs of the school and invited speakers who cover additional topics. The course consists of lecture-style elements and an interactive discussion and covers data science methods (such as clustering, image analysis, visualization, deep learning), domain-oriented methods (such as medical imaging, surgery) as well as ethical, legal and social implications. In addition, it will train researchers to consider the different views and needs of data science and health-related sciences, and the opportunities for interdisciplinary cooperation.
The following lecture course "Advanced Topics in Data Science & Health" has two objectives. On the one hand, it provides advanced doctoral researchers and postdocs with the opportunity to gain some experience in this type of teaching format. On the other hand, it will provide first-year doctoral researchers with an overview of recent scientific developments and the state of the art in the research fields of the presenters.
In addition, we will offer a set of specific scientific courses (for example, on Simulation & Optimization, Machine Learning, Uncertainty Quantification, Scientific Visualization, Python, Confocal Microscopy, International Zebrafish and Medaka Course) with a data and/or life science orientation.
The exact configuration of these compulsory elective courses is individually chosen by the doctoral researcher depending on thematic needs and existing skills.
Each doctoral researcher of the school should complete a funded mobility phase of around three months, either at a leading international university or institution. The school supports the selection of appropriate partner institutions, for example, using existing international cooperation networks such as HeKKSaGOn (the Heidelberg – Kyoto – Karlsruhe – Sendai – Göttingen – Osaka network of German and Japanese universities) and InterACT (network of eight universities from Europe, Asia and America including KIT and Carnegie Mellon University). DKFZ has exchange programs with the Weizmann Institute of Science (Israel), the MD Anderson Cancer Center (USA) and partners of Cancer Core Europe.
Each doctoral researcher is expected to attend at least one summer school, which will be held annually. These summer schools will be co-organized with other data science schools within HIDA, thus enabling all Helmholtz Information and Data Science School participants to network and encourage further collaboration.
Personal Skill Training
The school provides a wide portfolio of personal skills training (including leadership and language) as well as comprehensive support measures regarding internationalization, networking and career orientation. Courses such as “Introduction to German Academic Culture”, “Publishing in Scientific Journals”, and “Managing Projects” are currently offered. Furthermore, research school doctoral researchers will be encouraged to participate in the centrally-organized Helmholtz Transferable Skills Training program for doctoral researchers. Three modules, each lasting 2–3 days will provide training in (I) research skills development, (II) presentation and communication and (III) career and leadership.
Cross Theme Topics
Cross Theme Topics (CTTs) are a collaboration between 2–4 doctoral researchers working on related methodological problems, supported and mentored by postdocs and PIs of the school. The aim of a CTT is to leverage synergy potentials between projects (for example by sharing special skills of a doctoral researcher between projects) and to broaden the individual methodological understanding beyond the research areas. The ideal outcome of a CTT would be a joint paper, software tool or benchmark dataset. All doctoral researchers in HIDSS4Health will be encouraged to be involved in at least one CTT during his/her time in the school.
Winter semester 2019/2020 – Data Science & Health⎙
This lecture is held by the PIs of the school and invited speakers who cover additional themes. The course consists of lecture-style elements and an interactive discussion. It covers data science methods (e.g., clustering, image analysis, visualization, deep learning), domain-oriented methods (e.g., medical imaging, surgery) as well as ethical, legal and social implications. The aim of the course is to introduce the doctoral researchers to the field and to give a basic understanding of all research areas of the school. In addition, it will train them to consider the different views and needs of data science and health-related sciences, and the opportunities for interdisciplinary cooperation.
The lectures take place at the following locations:
- KIT: Geb 30.28, seminar room 004, Wolfgang-Gaede-Straße 6, 76131 Karlsruhe
- Mathematikon: Interdisziplinäres Zentrum für Wissenschaftliches Rechnen IWR, conference room 5.104, Im Neuenheimer Feld 205, 69120 Heidelberg
- DKFZ: main building, room H824 (8th floor), Im Neuenheimer Feld 280, 69120 Heidelberg
|2019-10-22||09:45–11:15||KIT||Ralf Mikut||Time Series Analysis|
|2019-10-22||11:30–13:00||KIT||Lennart Hilbert||Fluorescence microscopy and digital image processing in molecular cell biology|
|2019-11-05||09:45–11:15||Mathematikon||Carsten Rother||Image-based Machine Learning|
|2019-11-05||11:30–13:00||Mathematikon||Klaus Maier-Hein||Radiologic Data Science|
|2019-11-19||09:45–11:15||KIT||Achim Streit||Introduction to Distributed and Parallel Computing|
|2019-11-19||11:30–13:00||KIT||Peter Sanders||Parallel Algorithms for Dummies|
|2019-12-03||09:45–11:15||Mathematikon||Holger Fröning||Any Growth is Bounded – On the Future of Performance Scaling|
|2019-12-03||11:30–13:00||Mathematikon||Lena Maier-Hein||Surgical Data Science|
|2019-12-17||09:45–11:15||KIT||Franziska Mathis-Ullrich||Minimally-Invasive Robots for Medicine|
|2019-12-17||11:30–13:00||KIT||Tamim Asfour||Data-Driven Learning of Sensorimotor Skills for Robots and Exoskeletons|
|2020-01-07||09:45–11:15||Mathematikon||Michael Gertz||Introduction to Text Analysis|
|2020-01-07||11:30–13:00||Mathematikon||Robert Strzodka||Essential Performance Considerations in Programming|
|2020-01-21||09:45–11:15||KIT||Anne Koziolek||Requirements Engineering for Data-driven Solutions|
|2020-01-21||11:30–13:00||KIT||Ali Sunyaev||Introduction to Decentralized Data Management with Distributed Ledger Technology|
|2020-02-04||09:45–11:15||DKFZ||Martin Frank||Mathematical Aspects of Uncertainty Quantification|
|2020-02-04||11:30–13:00||DKFZ||Filip Sadlo||Introduction to Visual Data Science|
We will perform an annual candidate selection process, announcing 9 open positions in 2020 (details about the projects can be found in this document). We will select candidates in a four-step process: (1) the written application, (2) an optional Skype interview for shortlisted candidates, (3) an on-site selection event, and (4) matching projects and candidates. Evaluation criteria for the candidates are an excellent academic record and a strong motivation for the interdisciplinary nature of the projects. The institutions are committed to increasing the percentage of female scientists and encouraging female applicants to apply.
|Feb 17, 2020||Deadline for written applications|
|Apr 8, 2020||Selection Event in Heidelberg|
|May 1 – Sep 30, 2020||Start of Doctoral Researchers|
|Winter semester 2020/2021||Start Courses & Training Program|
Living in Heidelberg / Karlsruhe
Heidelberg and Karlsruhe are attractive cities located in the sunny south-western part of Germany within a traveling distance of around 50 kilometers. They are connected via a dense public transport network. More information on living costs can be found in the information pages of the German Academic Exchange Service (DAAD) or in a PDF booklet from the German Federal Ministry for Education and Research.
- Download and complete the application form, which also contains information about additional documents required:
- Print, sign and scan the Data Protection Consent Form:
- Submit the application form, required additional documents and signed consent here:
- Ask two independent referees for submission of reference letters (these should be sent to us directly by the referee, same deadline as the application):
We are looking for excellent graduates holding master degrees, received by July 2020 at the latest, in computer science, mathematics, engineering, physics or related quantitative sciences (e.g., bioinformatics or medical informatics).
All positions are fully-funded (e.g. “E13” TVöD or TV-L positions under applicable regulations of the participating institutions) according to the public sector salary system at German universities and research centers. It means a yearly gross income of more than 45.000 € and results in more than 26.000 € net income after taxes, own contributions to health insurance, pension insurance, unemployment insurance etc. Weekly working times are 39.5 hrs, the contract includes 30 paid leave days. However, since the German system is quite complicated, all financial details cannot be provided here but can be calculated here (sorry, only available in German).
Becoming an Associated Doctoral Researcher
You are already funded and your doctoral research is on a topic that is relevant to the school? Apply for an association!
Diversity and Equal Opportunities
The provision of equal opportunities and diversity is a central concern of KIT, DKFZ and Heidelberg University. We are committed to enabling researchers to balance the demands of career and family life and therefore offer various options to staff, such as flexible working time models, family-friendly meeting times, re-entry after maternity leave, comprehensive childcare concepts, provision of Tele-offices, parent-child offices, and in-house childcare facilities. Funded places in local childcare facilities offer full-time and part-time child-care (for example during a conference or summer school). The networks of female scientists at the partners – “WiKIT” at the KIT and the Executive Women’s Initiative at the DKFZ – are professional networks of female scientists in leading positions. These networks are platforms of mutual exchange and aim at fostering networking among female scientists of various disciplines to improve the career perspectives and working conditions of female scientists in Germany. All measures promoting the compatibility of career and family life are monitored and advanced by the “familiengerechte Hochschule” (family-friendly university) audit and “Audit Beruf und Familie” (Career and Family Audit) at the KIT, Heidelberg University and DKFZ, respectively.
List of relevant events for the school hosted by the school itself or by partner institutions.
WiDS Datathon 2020
- 3 days
More information here.
HIDA Datathon for Grand Challenges on Climate Change
- 2 days
HIDSS4Health Selection Event
- 1 day
Second round on-site internal selection event for invited candidates.
Healthcare Hackathon in Mainz
- 3 days
More information here.
Bioinformatics Career Day
- 1 day
More information will be available soon on www.dkfz.de/careerday.
Summer school on deep learning for medical imaging
- 8 days
More information about the school and the application procedure can be found here. Please note that the International Conference on Medical Imaging with Deep Learning follows directly after the school and might also be of interest.
ICVSS 2020 (International Computer Vision Summer School)
- 7 days
More information about the school and the application procedure can be found here.
Machine Learning Summer School-Indonesia
- 7 days
More information about the school and the application procedure can be found here.
Phone: +49 721 608-25731
Phone: +49 6221 42-2327