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Stellenangebote

PhD candidate position in Data Science/ Bioinformatics [Uni Basel]

A PhD candidate position is available at the Transfaculty Research Platform Molecular and Cognitive Neuroscience (MCN, www.mcn.unibas.ch/) of the University of Basel. MCN focuses on the neurobiological underpinnings of human behaviour and on the development of novel treatment options for neuropsychiatric disorders. Our research is enabled by our in-house computational platform which provides access to multi-omic data sets from preclinical data, clinical trials as well as in-house and public genomics and brain imaging data.
The research project will focus on extending and utilizing our existing computational analytics platform for reproducible research. The successful candidate will collaborate with bioinformaticians, statisticians, psychologists, and biologists to identify critical research questions and address them via computational approaches.‬ ‬‬‬‬‬‬‬‬‬
The successful candidate will have a Master's degree (or comparable) and a strong background in Data Sciences, Bioinformatics, Computer Science, Statistical Genetics, Neuroscience or related disciplines. The ideal candidate will have demonstrated hands-on experience of programming in R and SQL, experience in using git and Linux as well as affinity to statistical (genetics) methods. While English language skills are essential, German language skills are useful but not essential.
We offer the opportunity to work, study, and do research in an excellent, highly interdisciplinary scientific environment supported by research group leaders and staff. The Basel area is a sunny and cosmopolitan region in the Northwest of Switzerland right next to France and Germany and the University of Basel offers internationally competitive salaries.
Applications should be submitted electronically including your CV, research experience and the names of two references to Dr. Thomas Schlitt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!
www.unibas.ch

PhD position in Machine Learning for Genomics [Gagneur lab]

A PhD position is available in the Computational Biology group of the Technical University of Munich (Prof. Julien Gagneur) starting immediately.

 

Your role
You will develop computational methods and models expanding Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics [1]. Kipoi builds on a 3-way collaboration with international partners (Stegle lab, EMBL Heidelberg, and Kundaje lab, Stanford). The Kipoi model repository at https://kipoi.org is increasingly used and extended by the research community.

 

Research topics include: expressive mathematical representations of RNA or protein encoded regulatory sequences using deep learning approaches (e.g. [2]); integrative models of individual steps of gene expression; methodologies for interpretability of deep learning models, and for their application to the prediction of causal effects of genetic variants in rare or common diseases (e.g. [3]). We expect applications on large-scale public data and on unpublished datasets from experimental collaborators in biology (e.g. [4]) or medicine (e.g. [5]).

 

You are
Applicants must hold a master in bioinformatics, or in physics, statistics, or applied mathematics with a genuine interest in applications to genomics. (S)he should have know-how in machine learning or statistical modeling and demonstrated programming experience with R or python. (S)he should have excellent communications skills and work within an interdisciplinary setting.

 

We are
The Gagneur lab is a lively, international, and interdisciplinary computational biology group with a research focus on the genetic basis of gene regulation and its implication in diseases. We are located in the informatics department of the Technical University of Munich, one of the top ranked European universities. Our lab has strong links to other local scientists and institutions in biology and medicine. Munich offers an outstanding, dynamic, interactive and internationally oriented research environment. Munich, the 2018 “most livable city in the world” according to the urban magazine Monocle, and the proximity of the Alps provide an excellent quality of life.

 

Apply
The position is funded from core funding with a salary according to the TV-L (German academic salary scale). We encourage joining the graduate school QBM (Quantitative Bioscience Munich). Applications including a cover letter, CV, and references must be sent to Julien Gagneur (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!, cc: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) until Nov 30th 2018 referring to “PhD-Kipoi18” in the title.

 

More

 

1. Avsec et al., Kipoi: accelerating the community exchange and reuse of predictive models for genomics, bioRxiv, 2018
2. Avsec et al., Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks, Bioinformatics, 2017
3. Cheng et al., Modular modeling improves the predictions of genetic variant effects on splicing, bioRxiv, 2018 – winner model of the CAGI 2018 splicing challenge
4. Schwalb et al., TT-seq maps the human transient transcriptome, Science, 2016
5. Kremer et al., Genetic diagnosis of Mendelian disorders via RNA sequencing, Nature communs, 2017

 

 

3-year Post-doc position in Machine Learning for Genomics [Gagneur lab]

Your role
You will develop computational methods and models expanding Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics [1]. Kipoi builds on a 3-way collaboration with international partners (Stegle lab, EMBL Heidelberg, and Kundaje lab, Stanford). The Kipoi model repository at https://kipoi.org is increasingly used and extended by the research community.

The position is funded via the recently awarded research network MechML. Research topics include: expressive mathematical representations of RNA or protein encoded regulatory sequences, notably using deep learning approaches (e.g. [2]); development of integrative models of individual steps of gene expression; development of methodologies for interpretability of deep learning models, and for their application to the prediction of causal effects of genetic variants in rare or common diseases (e.g. [3]). We expect applications on large-scale public data and on unpublished datasets from experimental collaborators in biology (e.g. [4]) or medicine (e.g. [5]).

You are
Applicants must either hold a PhD in bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience with deep learning methods and application to real world high-dimensional data. (S)he must have a proven publication record, interest for translational research, and can work independently and creatively. (S)he should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting.

We are
The Gagneur lab is a lively, international, and interdisciplinary computational biology group with a research focus on the genetic basis of gene regulation and its implication in diseases. We are located in the informatics department of the Technical University of Munich, one of the top ranked European universities. Our lab has strong links to other local scientists and institutions in biology and medicine. Munich offers an outstanding, dynamic, interactive and internationally oriented research environment. Munich, the 2018 “most livable city in the world” according to the urban magazine Monocle, and the proximity of the Alps provide an excellent quality of life.

Apply
The position is funded for three years with a salary according to the TV-L (German academic salary scale).

Applications including a cover letter, CV, and references must be sent to Julien Gagneur (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!, cc: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) until Nov 30th 2018 referring to “Postdoc-mechML” in the title.

More

1. Avsec et al., Kipoi: accelerating the community exchange and reuse of predictive models for genomics, bioRxiv, 2018
2. Avsec et al., Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks, Bioinformatics, 2017
3. Cheng et al., Modular modeling improves the predictions of genetic variant effects on splicing, bioRxiv, 2018 – winner model of the CAGI 2018 splicing challenge
4. Schwalb et al., TT-seq maps the human transient transcriptome, Science, 2016
5. Kremer et al., Genetic diagnosis of Mendelian disorders via RNA sequencing, Nature communs, 2017
 

PhD position in Computational Biology for Genetic Disorders [Gagneur lab]

A PhD position is available in the Computational Biology group of the Technical University of Munich (Prof. Julien Gagneur) starting as soon as possible.

Your role
You will develop computational methods and analyse multi-omics datasets (genome, transcriptome, proteome, metabolome) to unravel the genetic and molecular basis of genetic disorders. Your research topics include: Detection of aberrant molecular events in multi-omics dataset, generalizing our software OUTRIDER for RNA-seq to multiple omics data modalities [1]; development of genetic variant and gene prioritization algorithms by integrating multi-omics data together with deep learning models of regulatory variants, leveraging the model repository of machine learning models for genomics Kipoi (https://kipoi.org, [2]); Integration of multi-omics with wearable sensor data in the context of a new research network with Stanford (Lars Steinmetz lab). You will work directly on patient data, in tight collaboration with two close collaborators: Dr. Holger Prokisch, who is coordinating the European consortium for mitochondrial disorder GENOMIT (example collaboration [3]), and Prof. Christoph Klein, head of the Children’s Hospital of the University of Munich (example collaboration [4]).

You are
Applicants must hold a master in bioinformatics, or in physics, statistics, or applied mathematics with a genuine interest in applications to genomics. We expect know-how in machine learning or statistical modeling and demonstrated programming experience with R or python.  (S)he should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting (biologists and geneticists).

We are
The Gagneur lab is a lively, international, and interdisciplinary computational biology group with a research focus on the genetic basis of gene regulation and its implication in diseases. Our group is located in the informatics department of the Technical University of Munich, one of the top ranked European universities. Our lab has strong links to other local scientists and institutions in biology and medicine. Munich offers an outstanding, dynamic, interactive and internationally oriented research environment. Munich, the 2018 “most livable city in the world” according to the urban magazine Monocle, and the proximity of the Alps provide an excellent quality of life.

Apply
The position is funded from core funding with a salary according to the TV-L (German academic salary scale). We encourage joining the graduate school QBM (Quantitative Bioscience Munich). 

Applications including a cover letter, CV, and references must be sent to Julien Gagneur (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!, cc: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) until Nov 30th 2018 referring to “PhD-rare18” in the title.

More
https://www.gagneurlab.in.tum.de
https://kipoi.org
https://qbm.genzentrum.lmu.de
1. Brechtmann et al., OUTRIDER: A statistical method for detecting aberrantly expressed genes in RNA sequencing data, AJHG, in press and bioRxiv
2. Avsec et al., Kipoi: accelerating the community exchange and reuse of predictive models for genomics, bioRxiv, 2018
3. Kremer et al., Genetic diagnosis of Mendelian disorders via RNA sequencing. Nature communs, 2017
4. Witzel et al., Chromatin remodelling factor SMARCD2 regulates transcriptional networks controlling early and late differentiation of neutrophil granulocytes, Nature Genetics, 2017

Post-doc position in Computational Biology for Genetic Disorders [Gagneur lab]

Your role
You will develop computational methods and analyse multi-omics datasets (genome, transcriptome, proteome, metabolome) to unravel the genetic and molecular basis of genetic disorders. Your research topics include: Detection of aberrant molecular events in multi-omics dataset, generalizing our software OUTRIDER for RNA-seq to multiple omics data modalities [1]; development of variant and gene prioritization algorithms by integrating multi-omics data together with deep learning models of regulatory variants, leveraging the model repository of machine learning models for genomics Kipoi (https://kipoi.org, [2]); Integration of multi-omics with wearable sensor data in the context of a new research network with Stanford (Lars Steinmetz lab). You will work directly on patient data, in tight collaboration with two close collaborators: Dr. Holger Prokisch, who is coordinating the European consortium for mitochondrial disorder GENOMIT (example collaboration [3]), and Prof. Christoph Klein, head of the Children’s Hospital of the University of Munich (example collaboration [4]).

 

You are
Applicants must either hold a PhD in computational biology, or hold a PhD in physics, statistics, or applied mathematics with practical experience with real world high-dimensional data analysis. Applicants with a PhD in biology with strong quantitative skills and demonstrated  experience with genetics and analysis of sequencing data will also be considered. The candidate must have a proven publication record, interest for translational research, and have demonstrated the ability to work independently and creatively. (S)he should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting, communicating with biologists and geneticists.

 

We are
The Gagneur lab is a lively, international, and interdisciplinary computational biology group with a research focus on the genetic basis of gene regulation and its implication in diseases. We are located in the informatics department of the Technical University of Munich, one of the top ranked European universities. Our lab has strong links to other local scientists and institutions in biology and medicine. Munich offers an outstanding, dynamic, interactive and internationally oriented research environment. Munich, the 2018 “most livable city in the world” according to the urban magazine Monocle, and the proximity of the Alps provide an excellent quality of life.

 

Apply
The position is funded from core funding with a salary according to the TV-L (German academic salary scale).

 

Applications including a cover letter, CV, and references must be sent to Julien Gagneur (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!, cc: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) until Nov 30th 2018 referring to “Postdoc-rare18” in the title.

 

More

1. Brechtmann et al., OUTRIDER: A statistical method for detecting aberrantly expressed genes in RNA sequencing data, AJHG, in press and bioRxiv

2. Avsec et al., Kipoi: accelerating the community exchange and reuse of predictive models for genomics, bioRxiv, 2018
3. Kremer et al., Genetic diagnosis of Mendelian disorders via RNA sequencing. Nature communications, 2017

 

4. Witzel et al., Chromatin remodelling factor SMARCD2 regulates transcriptional networks controlling early and late differentiation of neutrophil granulocytes, Nature Genetics, 2017

Bioinformatics position at University of Cologne

The Collaborative Research Center Predictability in Evolution is a leading consortium in experimental and theoretical studies of evolutionary processes. We focus on fast evolution in microbial, viral, cancer, and immune systems, which have a wide range of biomedical applications. At University of Cologne (Germany) and its partner institutions, the DFG-funded Center unites a strong and interdisciplinary spectrum of competence in molecular genetics, biophysics, medicine, and theoretical modelling. All members take full benefits of the Center’s joint research and training facilities.

We are looking for an excellent computational biologist to play an integral part in the science of our Center. If you enjoy bringing top-notch computational analysis to exciting projects, to play an active part in planning and analysis of experiments and modelling, and to discuss your results in a vibrant community, this position is for you. Specifically, you will develop powerful project-specific analysis for high-throughput data (e.g. deep sequencing data), train other scientists in using those methods, and implement user-friendly interfaces for broader use of new algorithms developed in the consortium. You should have a doctoral degree in a relevant field and a track record demonstrating programming skills and experience with the analysis of molecular high-throughput data. Experience with the programming of user interfaces is also welcome. The salary is comparable to a post-doctoral scientist.

Applications and enquiries should be directed to Christa Stitz (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!). Applications should include a CV, a list of publications, and other relevant credentials. Two letters of recommendation should be sent independently. The call is open until a position is filled; preferential consideration will be given to applications received before December 1st, 2018.

The University of Cologne and its partner institutions are equal opportunity employers. Applicants with disabilities will be employed with preference, given equal qualification and capability. Applications from women are explicitly encouraged and will be given particular consideration.

Bioinformatician [Heinrich Pette Institute – Leibniz Institute for Experimental Virology]

The Heinrich Pette Institute – Leibniz Institute for Experimental Virology in Hamburg, Germany, is seeking a

Bioinformatician

to join its Next Generation Sequencing team at the next possible date. We are looking for a highly motivated and responsible individual with team spirit, preferentially with prior experience in genome informatics. Candidates must hold an academic degree (minimally MSc) in bioinformatics or related disciplines and should be proficient in programming and/or scripting languages. Excellent communication skills in the German and/or the English language are a principal requirement.

The position will be initially filled for 2 years, but can be extended after successful evaluation. Payment will be commensurate with experience according to public sector collective agreement (TV-AVH).

The successful candidate will join an enthusiastic and interdisciplinary team of researchers dedicated to the investigation of various human pathogenic viruses and related diseases. Responsibilities will include the provision of bioinformatic support for genome-scale research projects, in particular mapping, organization, annotation and integrated downstream analysis of genomic, trancriptomic and epigenomic next generation sequencing data. Where necessary, the candidate will implement customized pipelines and/or develop innovative solutions as required to permit interrogation of complex infection systems by next generation sequencing.

We offer work in a highly stimulating environment with state-of-the-art infrastructure, providing the successful applicant with unique opportunities to develop a strong work portfolio at the interface of pathogen and human genomic research.

 

Further information regarding this offer may be requested from Prof. Adam Grundhoff (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!). For general information about the Heinrich Pette Institute, please visit our web site at http://www.hpi-hamburg.de/.

Applications from individuals with equal professional qualification and competence will be preferred.

 

Applications (including motivation letter, curriculum vitae and reference letters or contact information for two referees) should be sent as a single PDF file via electronic mail (subject line: 'Bioinformatician job offer 1018') to (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) by November 15th, 2018. Late applications will be considered until the position is filled.

 

1 Computational Biologist and 1 Molecular Biologist [IMB]

The Institute of Molecular Biology gGmbH

 

funded by the Boehringer Ingelheim Foundation

 

 

2 Postdoc Positions available

1 Computational Biologist and 1 Molecular Biologist

non-coding RNA & R-loop epigenetics 

 

 

The Institute of Molecular Biology gGmbH (IMB) is a Centre of Excellence for Life Sciences, funded by the Boehringer Ingelheim Foundation. It is located within the campus of the Johannes Gutenberg-University, Mainz, Germany. The Niehrs laboratory studies regulation of DNA methylation, which plays important roles in development & disease. We have recently demonstrated a role for long non-coding RNAs and R-loop DNA:RNA hybrids in DNA methylation (Arab et al. 2014, Mol Cell, (2014) 55: 604-614).  In an ERC-funded project, we now aim to elucidate the mechanisms of DNA demethylation as well as the role played by long non-coding RNAs and R-loops in its regulation. See also  www.imb-mainz.de/research-at-imb/niehrs/research/ Candidates will make use of mouse embryonic stem cells (ESCs) to interrogate genome-wide the role of ncRNAs and R-loops in targeting GADD45a and the DNA demethylation machinery in the genome. We will use CRISPR/CAS9 mediated ESC mutants, as well as ChIP-seq, RNA-seq, bisulfite-seq to carry out multi- dimensional data analysis to address: Where in the genome does demethylation occur? What are the molecular determinants in ncRNA & Rloops involved in targeting? What are the cofactors involved? The project will involve strong interaction between the Molecular- and the Computational Biologist.

 

You have

·         PhD & publications in a relevant field

·         Sound experience in R scripting or Python (Computational Biologist)

·         Sound experience in molecular biology (Molecular Biologist)

·         Familiarity with Omics techniques or –analysis, or with ncRNAs or R-loops is advantageous

·         Excellent communication skills and good team spirit with the ability to solve problems independently

·         Fluent in English (spoken and written)

 

We offer

• An international and vibrant working environment

• Competitive salary

• Training opportunities

• Favourable pension scheme

 

To apply please send a single PDF file containing your cover letter stating research and career interests, CV, scans of your degrees (Germans: including copies of Abitur- & Diplom/Master Zeugnis), and contact details of 2 references to Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!. Informal enquires should be addressed to Prof. Christof Niehrs (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!).

 

Starting date: before April 2018


Duration:
Initially 3 years; option for further extension


Application Deadline:
31st December 2018

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 https://www.imb.de/jobs/datenschutzerklaerung-data-protection/

BYONOY SUCHT EINE/N SOFTWAREENTWICKLER/IN, HAMBURG, VOLLZEIT, AB SOFORT

DAS SIND WIR.

Wir sind ein junges Life Science Technologieunternehmen aus Hamburg, das sich auf die Entwicklung von innovativen Messinstrumenten spezialisiert hat. Unsere Instrumente kommen insbesondere in der klinischen Diagnostik aber auch in der Lebensmittelanalytik, der Medikamentenforschung oder der Grundlagenforschung zum Einsatz. Unser Ziel ist es, in den kommenden Jahren unser Portfolio an Instrumenten mit optischen Messverfahren zu erweitern und diese international zu vertreiben.

 

DARUM GEHT ES.

Du wirst die Verantwortung für die Entwicklung der Steuerungs- und Analysesoftware für unsere Messinstrumente übernehmen. Dabei wirst Du Teil eines Expertenteams sein, das an der Schnittstelle von Technologie, Life Science und Design innovative Produkte entwickelt. Konkret fallen folgende spannende Themengebiete in deinen Aufgabenbereich:

o             Konzipierung, Projektplanung und Umsetzung der Steuerungs- und Analysesoftware für Messinstrumente im Life Science Bereich

o             Implementierung der UI und der UX unter Berücksichtigung regulatorischer Anforderungen

o             Entwicklung von Algorithmen zur Datenanalyse

o             Kommunikation mit Kunden und Anwendern für Produktoptimierungen

 

WEN WIR SUCHEN.

o             Abgeschlossenes Studium der Informatik oder vergleichbare Qualifikation

o             Umfassende Erfahrung in der C++-Programmierung oder mit vergleichbaren objektorientierten Programmiersprachen

o             Erfahrungen mit Computer Vision sind wünschenswert

o             Hohes Maß an Selbstständigkeit, Eigeninitiative und Teamfähigkeit

o             Innovative Denkweise

 

DAS BIETEN WIR.

 

Bei uns bleibt es spannend: Dich erwarten herausfordernde und vielseitige Aufgaben in einem dynamischen und wachsenden Start-Up-Umfeld. Wir sind ein junges Team mit positiver Arbeitsatmosphäre in einem modernen Arbeitsumfeld im Herzen Hamburgs.

 

UND JETZT?

 

Wenn wir dein Interesse geweckt haben, dann sende bitte deine vollständigen Bewerbungsunterlagen (Anschreiben, Lebenslauf, Zeugnisse) mit Angabe deiner Gehaltsvorstellung und des nächstmöglichen Eintrittstermins an Yousef: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!. Weitere Informationen findest du auf unserer Homepage unter www.byonoy.com

Post-Doc: Zentrum für Bioinformatik, Abt. Genominformatik, UHH

Fakultät: Fak. für Mathematik, Informatik und Naturwissenschaften

Einrichtung: Zentrum für Bioinformatik, Abteilung für Genominformatik

 

Ab dem 5.12.2018 ist die Stelle einer/eines  wissenschaftlichen Mitarbeiterin/Mitarbeiters gemäß § 28 Abs. 2 Hamburgisches Hochschulgesetz (HmbHG) in einem Post-Doc-Arbeitsverhältnis zu besetzen.

Die Vergütung  erfolgt nach der Entgeltgruppe  13 TV-L. Eine Verbeamtung  auf Zeit gemäß § 28 Abs. 2 HmbHG  ist bei Verfügbarkeit einer entsprechenden  Stelle und bei Vorliegen der beamtenrechtlichen

Voraussetzungen auf Antrag möglich.

 

Die wöchentliche Arbeitszeit beträgt 39 Stunden bzw. 40 Stunden bei einer Verbeamtung.

 

Die Befristung des Vertrages erfolgt auf der Grundlage von § 2 Wissenschaftszeitvertragsgesetz. Die Befristung ist vorgesehen für zunächst 3 Jahre. Eine Verlängerung um bis zu 3 Jahre ist bei positiver Bewertung der in der ersten Phase erbrachten Leistungen vorgesehen.

 

Die Universität strebt die Erhöhung des Anteils von Frauen am wissenschaftlichen Personal an und fordert deshalb qualifizierte Frauen nachdrücklich auf, sich zu bewerben. Frauen werden im Sinne des Hamburgischen Gleichstellungsgesetzes bei gleichwertiger Qualifikation vorrangig berücksichtigt.

 

Aufgaben:

Die Aufgaben umfassen wissenschaftliche Dienstleistungen in der Forschung und der Lehre im Fachbereich bzw. in der wissenschaftlichen Einrichtung. Im Rahmen des Beschäftigungsverhältnisses besteht Gelegenheit zur Erbringung zusätzlicher wissenschaftlicher Leistungen durch selbständige Forschung sowie zum Erwerb von Erfahrungen in der Lehre. Im Rahmen der Dienstaufgaben wird daher ein Zeitanteil von mindestens einem Drittel der vertraglich vereinbarten Arbeitszeit zur eigenen wissenschaftlichen Arbeit gewährt.

 

Aufgabengebiet:

Von der Stelleninhaberin/dem Stelleninhaber wird eine engagierte Beteiligung an der Forschung und der Lehre (4 LVS) im Zentrum für Bioinformatik (ZBH) erwartet. Die Forschungstätigkeit erfolgt im Themengebiet der Genominformatik.

 

Einstellungsvoraussetzungen:

Abschluss eines den Aufgaben entsprechenden Hochschulstudiums, Promotion (z.B. in Bioinformatik oder Informatik), sehr gute Deutsch- und Englischkenntnisse, fundierte methodische Kenntnisse der Bioinformatik insbesondere im Bereich der Analyse von Genomsequenzen und genomischen Daten, sehr gute Programmierkenntnisse, Erfahrung in der Entwicklung großer Softwaresysteme, sowie Erfahrung bei der Präsentation wissenschaftlicher Ergebnisse.

 

Schwerbehinderte haben Vorrang vor gesetzlich nicht bevorrechtigten Bewerberinnen/Bewerbern bei gleicher Eignung, Befähigung und fachlicher Leistung.

 

Für nähere Informationen wenden Sie sich bitte an Prof. Stefan  Kurtz, (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) oder schauen Sie im Internet unter http://www.zbh.uni-hamburg.de/ nach.

 

Bitte senden Sie Ihre Bewerbung mit den üblichen Unterlagen (Bewerbungsschreiben,  tabellarischer Lebenslauf, Hochschulabschluss) bis zum 31.10.2018 an:

 

Universität Hamburg

Zentrum für Bioinformatik

Prof. Dr. Stefan Kurtz

Bundesstrasse 43

20146 Hamburg