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Ph.D. Student in Biomedical Data Science (HCV)

The Chair for Methods in Medical Informatics (Prof. Dr. Nico Pfeifer), Department of Computer Science at Eberhard Karls University Tübingen, one of eleven German universities distinguished as excellent under the German government’s initiative, is currently looking for a


Ph.D. Student in Biomedical Data Science (HCV) (E13 TV-L, 65%)


starting as soon as possible. The initial fixed-term contract will be for 2 years with possible extension. The position is funded by the German Center for Infection Research (DZIF).


The prescription of direct-acting antiviral agents is associated with high rates of sustained virological response (SVR) in patients treated against hepatitis C virus (HCV). Treatment failure is associated with the presence of resistance-associated mutations (RAMs), which can emerge during treatment or be transmitted. The use of genotypic drug resistance tests such as geno2pheno[hcv] or geno2pheno[ngs-freq], which identify RAMs in the amino-acid sequences of the non-structural (NS) proteins NS3, NS5A, and NS5B, can guide treatment decisions. The successful candidate will use statistical methods to analyze next-generation sequencing (NGS) data and apply and extend state-of-the-art machine learning methods to further improve upon current genotypic systems.


The group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. Nico Pfeifer is a PI in the excellence cluster “Machine Learning: New Perspectives for Science” starting in January 2019. We are developing methods that allow answering new biomedical questions (Speicher and Pfeifer 2015, Proceedings of ISMB/ECCB 2015) and optimize them in close contact with our excellent national and international biomedical partners (Carlson et al. 2016, Nature Medicine, Schoofs et al. 2016, Science, Döring et al. 2016, Retrovirology, Mendoza et al. 2018, Nature).



The ideal candidate will have an M.Sc. or equivalent in Biomedical Data Science, Biometry, Biostatistics, Bioinformatics, Medical Informatics, Computer Science, Computational Biology or a related life science discipline. Applicants should have an interest in interdisciplinary work. Experience in data science and machine learning as well as strong programming/scripting skills (C/C++, R, Matlab, Python, JavaScript, Java) are desirable. Other relevant qualifications include:

  • Background in Statistics

  • Experience with medical data (clinical data, molecular data, …)

  • Experience with high-throughput data (next-generation sequencing)

  • Databases (MySQL, NoSQL)

Knowledge of the adaptive immune system is a plus.


In case of equal qualification and experience, physically challenged applicants are given preference. The University of Tübingen aims at increasing the share of women in science and encourages female scientists to apply. Candidates will be officially employed by the administration of the University of Tübingen.


Please send your application (including motivation letter, curriculum vitae, transcripts and certificates, and contact details of two academic references) via e-mail to
This email address is being protected from spambots. You need JavaScript enabled to view it. with the subject: Ph.D. student application Biomedical Data Science (HCV).


Application deadline: December 21st, 2018.

Candidates are encouraged to send their application material early since we will start reviewing applications already before the deadline.

3 PhD Student Positions in the Computational Plant Sciences []

The International Max Planck Research School (IMPRS) on ‘Understanding Complex Plant Traits using Computational and Evolutionary Approaches’ is a local collaboration between the Max Planck Institute for Plant Breeding Research (MPIPZ) and the Universities in Cologne and Düsseldorf (Germany). The IMPRS has been established in 2002 and offers an international PhD programme in English. Students are closely supervised through an advisory committee, receive professional training in transferable and applicable skills and are supported to share their scientific insights.
Our common goal is to understand the molecular basis of complex traits that differ between plant species and confer novel phenotypic characteristics. Computational approaches have become an integral part of our research, reflected by a continuously growing number of related projects and groups. The advertised projects will be performed in the groups of Angela Hancock (, Xiangchao Gan ( and Stefan Laurent ( & and applicants have the opportunity to indicate a preference in the online application process.
You are a highly qualified and motivated student from any nationality with an MSc (or equivalent) degree in a related subject such as bioinformatics and population/quantitative genetics. You have a proved track record of academic and research excellence and are fluent in written and spoken English. Additionally, you have experience with one or more programming languages such as Python, Java, C/C++ and R.
We provide an excellent and interdisciplinary research environment with a state-of-the-art IT infrastructure. The positions are fully funded for 3 years with possible extension. We are committed to increasing the number of individuals with disabilities in the workforce and encourage applications from such qualified individuals. We furthermore seek to increase the number of women in those areas where they are underrepresented and therefore explicitly encourage women to apply.
Apply by January 4, 2019 at Only applications submitted through the online platform will be considered. Shortlisted candidates will be invited to the MPIPZ for interviews on March 18-21, 2019. Successful candidates will start their positions preferably on October 1, 2019.
Dr. Stephan Wagner (IMPRS co-ordinator) at This email address is being protected from spambots. You need JavaScript enabled to view it.
Apply online via and find additional information at

Bioinformatician [IMB]

The Institute of Molecular Biology gGmbH

funded by the Boehringer Ingelheim Foundation

is recruiting a

Bioinformatician (m/f)


The Institute of Molecular Biology gGmbH (IMB) is a Centre of Excellence for Life Sciences funded by the Boehringer Ingelheim Foundation. IMB is located at the campus of the Johannes Gutenberg University in Mainz, Germany and offers premium scientific core facilities (see The Bioinformatics Core Facility supports IMB researchers in the computational analysis of genomic data generated in the course of research projects. We are looking for a highly motivated Bioinformatician (m/f) with enthusiasm for academic research to join our team and support a newly formed Collaborative Research Centre, CRC 1361, on the topic “Regulation of DNA Repair and Genome Stability”, funded by the German Research Foundation DFG (see

You will:

•             Join exciting CRC projects studying the mechanisms of DNA repair and genome stability

•             Participate in the experimental planning, processing, interpretation and publication of various genomic, epigenomic and transcriptomic next-generation sequencing (NGS) datasets

•             Develop and implement custom bioinformatics workflows for data analysis and integration


Required qualifications:

•             University degree or postgraduate training in computational biology / bioinformatics

•             Extensive and broad experience in the computational analysis of NGS datasets

•             Solid programming skills and familiarity with Linux compute clusters

•             Sound knowledge of statistics, version control and R / Bioconductor

•             Good organisational, communication and interpersonal skills

•             Proficiency in written and spoken English


Desirable qualifications:

•             Experience in interdisciplinary collaborations or bioinformatics services

•             Knowledge of software engineering and bioinformatics pipelines


We offer:

•             Stimulating, diverse and international research environment

•             Flexible working hours and advanced training opportunities

•             Competitive salary and favourable pension scheme


To apply, please send a single PDF file containing your cover letter, CV, certificates and contact information of at least two professional references quoting Ref. No. CFBIO15 to This email address is being protected from spambots. You need JavaScript enabled to view it.. IMB is an equal opportunity employer.


Starting Date:  as soon as possible

Duration:   initial contract for four years with the possibility of extension

Application Deadline:  20th January 2019


Declaration of Consent and Data Protection

By sending us your application, you are consenting to us saving your personal data in order to carry out the selection process. You can find more information on data protection and retention periods at Protection.




Wissenschaftliche/n Mitarbeiter/in (m/w/d) [Lehrstuhl für Epidemiologie/UNIKA-T]

Die Ludwig-Maximilians-Universität München ist eine der größten und renommiertesten Universitäten Deutschlands. Der Lehrstuhl für Epidemiologie/UNIKA-T, angesiedelt am Klinikum Augsburg, sucht zum nächstmöglichen Zeitpunkt eine/n



Wissenschaftliche/n Mitarbeiter/in (m/w/d)



Ihre Aufgaben:

·           Eigenständige Durchführung wissenschaftlicher Projekte zu Einflussfaktoren auf die Entstehung und den Verlauf von chronischen Krankheiten

·           Statistische Auswertung von großen Datensätzen (inklusive Omics-Daten)

·           Erstellung von wissenschaftlichen Publikationen und Berichten

·           Mitarbeit bei laufenden epidemiologischen Studien des Lehrstuhls


Ihr Profil:

·           Erfolgreich abgeschlossenes Hochschulstudium in den Bereichen Naturwissenschaft, Medizin oder verwandten Gebieten

·           Erfolgreich abgeschlossenes Zusatzstudium im Bereich Epidemiologie/Public Health

·           Praktische Erfahrungen in statistischer Datenauswertung (z.B. mit R oder SAS) und im Verfassen wissenschaftlicher Texte sind von Vorteil

·           Sehr gute Englischkenntnisse werden ebenso vorausgesetzt wie Kommunikationsfähigkeit, Teamgeist und Zuverlässigkeit



Unser Angebot:

Ihr Arbeitsplatz befindet sich am Campus des Klinikums Augsburg und ist gut mit öffentlichen Verkehrsmitteln zu erreichen. Wir bieten Ihnen einen interessanten und verantwortungsvollen Arbeitsplatz mit guten Weiterbildungs- und Entwicklungsmöglichkeiten.


Die Anstellung erfolgt befristet für 3 Jahre. Die Eingruppierung erfolgt nach dem TV-L, E13 (65%). Es besteht die Möglichkeit zur Promotion. Schwerbehinderte Bewerber/innen werden bei ansonsten im Wesentlichen gleicher Eignung bevorzugt. Die Bewerbung von Frauen wird begrüßt.


Bitte schicken Sie Ihre aussagekräftigen Bewerbungsunterlagen bis spätestens 07.01.2019 per Email an das Sekretariat des Lehrstuhls für Epidemiologie der LMU München am UNIKA-T, Frau Kötzner, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. Für dringende Rückfragen steht Ihnen die Lehrstuhlleitung unter der Telefonnummer 0821-598-6471 zur Verfügung.

PostDoc Position in Network Epigenomics

Full time position for a PostDoc to fill in the newly established group for Big Data in Biomedicine at the Chair of Experimental Bioinformatics, Technical University of Munich, Freising, Germany.
Project description
A major research barrier in systems biomedicine is that most of the currently used gene-gene interaction networks are not cell type-specific and neglect much of our current understanding of cellular regulation (i.e. enhancers and repressors). The EpiMap project of the International Human Epigenome Consortium currently integrates and harmonizes multi-omics data from 1000 epigenomes, offering a unique chance to overcome this barrier. The aim of this research project is to use state-of-the-art machine learning techniques for multitask and transfer learning to construct robust cell-type-specific molecular interaction networks. Such networks will allow researchers to put their experimental results in a cell type-specific context and thus pave the way towards adding an epigenetic perspective to biomedical research in general and to systems medicine in particular.
Your qualifications
- Recent PhD in Computational Biology, Bioinformatics, Genomics, Epigenetics or a related field. 
- Strong experience with handling RNA-seq, small RNA-seq, WGBS, RRBS, ChiP-seq data 
- Strong experience with systems biology and network analysis techniques
- Strong experience with advanced machine learning techniques, e.g. SVNs, RF, CNN
- Strong experience in R, Python or Java
- Good experience in using compute clusters / HPC environments and Docker / Singularity
- Solid understanding of molecular biology in general and epigenetic mechanisms in particular
- Ability to independently carry out a challenging research project in an international collaboration
- Fluency in English in written and spoken language.
What we offer
At the Chair of Experimental Bioinformatics you will find a supportive and productive research environment with a young, dynamic team of more than 20 international researchers at different stages in their career and education. Find us online at: and
The position is available starting immediately and initially limited for 3 year with a gross salary calculated according to A13 TV-L.
Interested? Send your application including your CV, the most relevant publications and two reference letters to This email address is being protected from spambots. You need JavaScript enabled to view it..
Links: URL for this position announcement:

Horizontal functional inference to leverage the metagenomic data deluge

The Soeding lab ( at the MPI for biophysical chemistry in Goettingen is looking to fill a positions for postdocs (E13 TVoeD Bund, three years), starting ~ 01/2019 or later, in methods development for metagenomics. 

Motivation: To predict the function of protein sequences in metagenomes, all common tools search for related sequences in the reference databases, from which the functional annotation can be inferred. But many species found in metagenomics studies are not closely related to any organism with a well-annotated genome. Therefore, the fraction of protein sequences in metagenomic data that cannot be annotated using this "vertical" information transfer is often as high as 65% to 90%.  This is the major obstacle to make progress.

Project: We want to develop a new paradigm for function prediction based on the transfer of contextual, ”horizontal” information. Building on our MMseqs2 software for fast sequence and profile searches [1] and sequence clustering [2], we will develop a very fast sequence search method that can find clusters of neighboring and co-transcribed genes. The basis idea of utilising genomic context is similar to well-known tools such as the STRING database. However, we are devising a novel statistical approach which, in combination with MMseqs2 and Linclust, will allow us to analyse huge numbers of genomes and metagenomes.  Using iterative profile searches combined with horizontal information transfer, we will mine massive amounts of genomic and metagenomic data to learn functional modules of genes / proteins that will subsequently be used for improved annotation. This novel approach promises to greatly accelerate the rate of biological and biotechnological discoveries by deep mining of metagenomic and genomic sequence data. 

Your profile: The project requires very good programming skills and interest in writing efficient, fast code. Experience with C++ and AVX2 is not required and can be learned on the job. Furthermore, an interest and some background in statistical approaches in bioinformatics will be highly useful. Women are particularly encouraged to apply. Applications from non-germans are very welcome. 
Our group: Our group of 3 postdocs, 6 PhD students, two master students and a PI develop statistical and computational methods for analyzing data from high-throughput biological experiments. You would join a team of 3 PhD students and a postdoc working on method development for metagenomics.

If you are interested I would be happy to hear from you!
Johannes Soeding <This email address is being protected from spambots. You need JavaScript enabled to view it.>
[1] Steinegger, M., and Söding, J. (2017) MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnol. 35, 1026–1028.
[2] Steinegger, M., and Söding, J. (2018) Clustering huge protein sequence sets in linear time. Nature Commun. 9, 2542.



PhD Positions in Computational Cancer Research in Heidelberg

Are you interested in solving fascinating biological or medical questions computationally?


At the German Cancer Research Center (DKFZ) in Heidelberg, Germany’s largest biomedical research institute, computational scientists work at the forefront of cancer research. They combine inter­disciplinary approaches from physics, biology, bioinformatics and statistics to analyze and understand complex biological and medical data.


Main activities at the DKFZ involving big data:

•             Development and application of computa­tional methods for the integrative analysis of genomic, epigenomic, transcriptomic, proteomic, meta­bolomic and radiomic data

•             Development of methods for modeling and simulation of biological and medical processes

•             DNA mutation analysis by next-generation DNA sequencing of individual human cancer genomes

•             Application of state-of-the-art technologies in automated live-cell imaging and image analysis

•             Computer-assisted radiology and surgery

•             Biostatistical evaluation of experimental and clinical data

•             Integration and development of new methods for systems biology and systems medicine


More information about computational research at the DKFZ can be found at:



Full funding is provided for the duration of the PhD.


If you are interested in doing your PhD in the field of computational cancer research, why not join the International PhD Program at the DKFZ with more than 500 PhD students?

More information about the program at



Application deadline: 5th January 2019

Postdoc: Bioinformatics, Cancer Genomics, Epigenomics, Precision Medicine

A full PDF version of this job posting is available from the following URL: 


Postdoc: Bioinformatics, Cancer Genomics, Epigenomics, Precision Medicine


We are recruiting an ambitious computational postdoc who wants to pursue groundbreaking research in bioinformatics and its applications in cancer research, including data analysis and methods development in the areas of genomics, epigenomics, and precision medicine. Our group at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna combines wet-lab biology/medicine including massive-scale data production (cancer genomes/epigenomes, single-cell sequencing, CRISPR screens) with advanced bioinformatics including data science algorithms and deep learning. We work closely with physicians at the Vienna General Hospital & Medical University of Vienna to advance cancer therapy by precision medicine.


The Project

Our lab has pioneered the combined use of high-throughput epigenomics and advanced computational methods for dissecting the epigenetic basis of cancer, toward the goal of enabling new approaches to precision medicine (Nature Reviews Cancer 2012).  In recent projects, we have connected epigenome and clinical imaging data for brain tumor progression (Nature Medicine 2018), investigated epigenetic heterogeneity in a cancer of childhood (Nature Medicine 2017), identified clinically predictive chromatin signatures in leukemia (Nature Communications 2016), and modeled the time series dynamics in leukemia response to therapy (paper in revision). All four papers were spearheaded and first-authored by bioinformaticians. Furthermore, we have developed technology that enables large-scale functional dissection using CRISPR single-cell sequencing (Nature Methods 2017) and drug screening (Nature Chemical Biology, in press). In ongoing and future work, for which the successful candidate will play a leading role, we are studying cancer immunotherapies, the tumor microenvironment, and time series of therapy response.


The Candidate

We are looking for ambitious candidates who want to build a scientific career in bioinformatics and/or data science research with applications in biology and medicine. Candidate should have a strong background in the quantitative sciences (computer science, bioinformatics, statistics, mathematics physics, engineering, etc.). We will also consider applicants with a background in biology or medicine who have strong quantitative skills (including programming) and a keen interest in pursuing computational projects (a combination with wet-lab research is possible).


The Lab (

The Medical Epigenomics Lab at CeMM pursues an interdisciplinary and highly collaborative research program aimed at understanding the cancer epigenome and establishing its utility for precision medicine. The lab is internationally well connected and active in several fields:

·         Bioinformatics. New computational methods enable the high-throughput analysis of disease mechanism and therapy responses. We develop algorithms for multi-omics data analysis, time series modeling, and clinical data integration.

·         Epigenomics. Many diseases show deregulation of epigenetic cell states. As members of the Human Cell Atlas and the International Human Epigenome Consortium, we use epigenome sequencing to dissect the epigenetic basis of cancer and immunity.

·         Technology. Groundbreaking biomedical research is frequently driven by new technologies. Our lab is therefore heavily invested into technology development, including single-cell sequencing, CRISPR screens, and deep neural networks.

·         Digital Medicine. New technologies in the area of genomics, imaging, and wearable sensors transform medicine into a ‘big data’ science. We employ machine learning / artificial intelligence to leverage such data for better patient care.


The Principal Investigator (

Christoph Bock is a principal investigator at CeMM. His research focuses on bioinformatics, epigenetics, cancer biology, and high-throughput technology development. He is also a guest professor at the Medical University of Vienna, scientific coordinator of the Biomedical Sequencing Facility at CeMM, and adjunct group leader for bioinformatics at the Max Planck Institute for Informatics. He is a member of the Young Academy of the Austrian Academy of Sciences (since 2017) and recipient of several major research awards, including the Max Planck Society’s Otto Hahn Medal (2009), an ERC Starting Grant (2016-2021), and the Overton Prize of the International Society of Computational Biology (2017).


The Institute (

CeMM is an international research institute of the Austrian Academy of Sciences and a founding member of EU-LIFE. It has an outstanding track record of top-notch science (last few years: >10 papers in Nature/Cell/Science/NEJM, >25 papers in Nature/Cell sister journals) and medical translation. With just over a hundred researchers, CeMM provides a truly collaborative and personal environment, while maintaining critical mass and all relevant technologies. Research at CeMM focuses on cancer, inflammation, and immune disorders. CeMM is located at the center of one of the largest medical campuses in Europe, within walking distance of Vienna’s historical city center. A study by “The Scientist” placed CeMM among the top-5 best places to work in academia world-wide ( Vienna is frequently ranked the world’s best city to live. It is a United Nations city with a large English-speaking community. The official language at CeMM is English, and more than 40 different nationalities are represented at the institute. CeMM promotes equal opportunity and harbors a mix of different talents, backgrounds, competences, and interests. Postdocs at CeMM are paid according to the Austrian Science Fund’s salary scheme, which amounts to an annual gross salary slightly above EUR 50,000.


Please apply online ( with cover letter, CV, academic transcripts, and contact details of three referees. Applications will be reviewed on a rolling basis. Any application received by 10 January 2019 will be considered. Start dates are flexible.


Research assistant/associate [University of Bonn]

In the frame of the collaborative research project DBAC (DNA-Barcode Analyzer for CITES Species), financed by the Federal Agency for Nature Conservation (BfN), the University of Bonn invites applications for a


Research assistant/associate (100%, TV-L E 13)


to begin on Febuary 1st, 2019 at the Nees Institute for Plant Biodiversity in the research group of Prof. Dr. Dietmar Quandt.


DBAC aims to develop a browser based open source analyses platform for DNA-barcode sequences generated via next generation sequencing (NGS). The standalone platform will also be embedded in the online resources of the West German Genome Center (WGGC) at the University of Bonn. Therefore, the applicant should be familiar with programming, NGS and bioinformatics. The research project runs in collaboration with the Institute for Human genetics, University Hospital Bonn (UKB), the Max Planck Institute (MPI) for Plant Breeding Research (MPIPZ), and the Institute for Evolutionary Biology, University of Münster.


The position's requirements are:

  • Diploma, or Master in (Bio)-Informatics or Biology, Plant Science, Evolutionary Biology, or related fields,

  • Preferably a PhD in one of the fields

  • Proven qualifications in programming and bioinformatics

  • Experience with next generation sequencing data and DNA-Barcoding

  • High motivation, active participation, commitment and interaction with the collaborative partners

  • Language skills: English (written and spoken)


Application documents:

  • Letter of motivation

  • Curriculum vitae

  • Transcripts of studies

  • Two letters of recommendation


The temporary position is limited to the duration of the research program and therefore restricted to a maximum duration of 12 months. Starting date of the position is February or latest March 1st, 2019.


The University of Bonn is an equal opportunities employer.


Applications in German or English should be sent in electronic form by December 10th, 2018 to Prof. Dr. Dietmar Quandt at the following e-mail address: This email address is being protected from spambots. You need JavaScript enabled to view it. (subject: DBAC Application).

Post-doc or Ph.D. Candidate in Single Cell Bioinformatics

The Institute for Computational Genomics RWTH Aachen  performs
research on computational methods for analysis of epigenomics and
transcriptomics data ( Over the past years, we have
developed methods for prediction of cell specific binding sites from
open chromatin data (Gusmao et al., Bioinformatics, 2015; Nature
Methods, 2016), inference of regulatory networks driving cell
differentiation (Lin et al., NAR, 2015; Allhoff et al.,
Bioinformatics, 2015) and prediction of long noncoding RNA regulation
via DNA-RNA interaction (Kalwa et al., NAR, 2016). We invite
applicants for a Posdoc or Phd Candidate position in Machine learning
methods for the analysis of single cell data. Candidates will perform
research on methods for analysis of single cell epigenomics and
transcriptomics scATAC-Seq, scRNA-Seq and scBS-seq. The project will
be performed in collaboration with medical specialists from the RWTH
Aachen University to understanding cellular changes during
inflammation and fibrosis and their support to cancer. The Institute
of Computational Genomics is a partner of the Human Cell Atlas

Applicants should hold a M.Sc. (Ph.D.) in Bioinformatics or Computer
Science. Experience in the analysis of biological sequences,
regulatory genomics and/or machine learning is required. The candidate
should have solid programming skills (C, Python and/or R) and
acquaintance with Linux. Experience with high performance computing is
a plus. The working language of the group is English. Interested
candidates should send a brief statement of research interests, CV and
the names of three references to This email address is being protected from spambots. You need JavaScript enabled to view it..
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