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Stellenangebote

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: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!. 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: https://www.exbio.de and https://biomedical-big-data.de.
 
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 Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!.
 
Links: URL for this position announcement: https://biomedical-big-data.de/post/job-announcement-nov18/

Horizontal functional inference to leverage the metagenomic data deluge

The Soeding lab (https://www.mpibpc.mpg.de/soeding) 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 <Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!>
 
 
[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.  https://doi.org/10.1038/nbt.3988
 
[2] Steinegger, M., and Söding, J. (2018) Clustering huge protein sequence sets in linear time. Nature Commun. 9, 2542.  https://doi.org/10.1101/104034
 
 
 

 

 

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:

https://www.dkfz.de/en/forschung/schwerpunkte/fsp-e.php?campaign=phd/bioinf

and

https://www.dkfz.de/en/forschung/schwerpunkte/fsp-b.php?campaign=phd/bioinf

 

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 http://www.dkfz.de/en/phd-program/index.html?campaign=phd/bioinf

 

 

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: http://www.medical-epigenomics.org/files/Postdoc_Bioinformatics_Genomics_Cancer.pdf 

 

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 (http://epigenomics.cemm.oeaw.ac.at/)

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 (https://scholar.google.com/citations?user=9qSsTcIAAAAJ)

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 (http://www.cemm.at/)

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 (http://the-scientist.com/2012/08/01/best-places-to-work-academia-2012). 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 (https://cemm.jobbase.io/job/6c6xaqal) 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: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! (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 (www.costalab.org). 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
Consortia.

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 Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!.

PostDoc Physics / Computer Science with a focus on Machine Learning / Deep Learning [Würzburg]

The Comprehensive Heart Failure Center Würzburg (CHFC) is an Integrated Research and Treatment Center supported by the German Ministry of Education and Research. More than 120 scientists conduct interdisciplinary basic, translational, and clinical research and provide innovative patient care in the field of prevention of heart failure and its medical complications. The CHFC’s vision is to improve the awareness of heart failure as an urgent health challenge in society, to connect existing excellent basic science and clinical research and to implement preventive strategies for diagnostics and management as well as new therapies. In 2017, the CHFC moved into a modern research building comprising four departments, i.e. imaging, translational research, genetics, and clinical research.

The PostDoc shall implement machine and deep learning algorithms for the image based prediction of heart diseases.

Successful candidates should have relevant experience in machine/deep learning, preferably in the area of medicine and/or image analysis and reconstruction.

Willingness to work in an interdisciplinary team of physicists, engineers, medical doctors and veterinarians as well as the active involvement in the continuation of the CHFC Imaging Facilities are absolute prerequisites. Previous experience in the field of magnetic resonance tomography and/or computational fluid dynamics would be greatly appreciated.

We offer an interesting and challenging task in a cutting-edge work environment with the possibility to contribute and extent your skills.

Payment will be according to individual qualification and the TV-L. Disabled applicants will be considered preferentially in case of equivalent qualifications.

Applicants should submit their complete application document (full CV including certificates, motivation letter, names and addresses of two references) in a single PDF file to:

Comprehensive Heart Failure Center, Am Schwarzenberg 15, Haus A15, 97078 Würzburg, preferably via email (all together in one single PDF document) to Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!. For further information please visit www.dzhi.de or contact Prof. Dr. Laura Schreiber (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!).

 

Links: www.dzhi.de

PhD and PostDoc position in computational cancer biology [European Institute of Oncoglogy (IEO) in Milan]

The lab of Martin Schaefer at the European Institute of Oncoglogy (IEO) in Milan is now recruiting two early-career scientists with a strong computational background. We are looking for one PhD student and one PostDoc.
The aim of the open positions is to further the understanding of cancer evolution by developing methods that allow to identify cancer driver events beyond point mutations (such as epigenetic changes or chromosomal rearrangements) and to apply these methods to experimental and clinical data. More details on the research interests of the lab can be found here: schaeferlab.org.
Candidates should have expertise in statistics, programming and the analysis of omics data. In particular, we encourage researchers with interest in either population genetics or network biology to apply.
The IEO is one of Europe’s leading cancer research institutes in a central location of Milan and hosts a vibrant, international research community. It provides postgraduate education through the European School of Molecular Medicine SEMM with a PhD program in Systems Medicine.
The positions are available immediately but the starting date can be negotiated. For more information see https://www.schaeferlab.org/misc/join/ or contact Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!.

Postdoc Position: Bioinformatics of Long Noncoding RNA Functional Elements

The “Genomics of Long Non-Coding RNAs in Disease” Laboratory (GOLD Lab) at the University of Bern has an opportunity for a Bioinformatics Postdoc.

The Project: Understanding how long noncoding RNA (lncRNA) functions are encoded in their sequence is a great challenge in biology. Our goal is to discover, classify and characterise lncRNA functional elements by means of an integrative bioinformatic / experimental approach. You will lead the bioinformatic component to develop novel methods for identifying lncRNA elements and predicting their functions. In collaboration our experimental team, you will have ample opportunities for experimental validation of in silico-generated hypotheses.

The Group: We are an international and interdisciplinary group of researchers with a passion for lncRNA research. We foster an open and collaborative working environment. Our work is funded by the Swiss National Center for Competence in Research (NCCR) “RNA & Disease” (nccr-rna-and-disease.ch), and we participate in the GENCODE project and International Cancer Genome Consortium (ICGC). We also have excellent biomedical links at the University Hospital of Bern. For more information about us: gold-lab.org / twitter.com/goldlab_bern

The City: Bern, the capital of Switzerland, has a vibrant international community, numerous outdoors and cultural activities, and ranks among the best cities worldwide for quality of life (https://tinyurl.com/y9vrtb7d).

The Person: We seek a dedicated and dynamic colleague to integrate into our diverse team. You should have strong background in bioinformatics or computer science, and specifically some/all of: Unix environment, R, perl/python, analysis of NGS data, webservers/databases. Experience in lncRNAs, CRISPR-Cas9 is a plus.

Details: Ideal start date will be Q1 of 2019. Project is fully funded for 4 years. Salary is according to (generous) University of Bern scales.

Recent publications:

Carlevaro-Fita et al. Biorxiv https://www.biorxiv.org/content/early/2017/10/23/189753

Uszczynska-Ratajczak B et al. Nat Rev Genet. 2018 Sep;19(9):535-548. doi: 10.1038/s41576-018-0017-y.

Lagarde J et al. Nat Genet. 2017 Dec;49(12):1731-1740. doi: 10.1038/ng.3988.

To apply: Please send a motivation letter, publications list, list of references, and CV to Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! with subject title: “Job application Bioinformatics Postdoc”. Informal enquiries are also welcome.