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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 We expect applications on large-scale public data and on unpublished datasets from experimental collaborators in biology (e.g. [4]) or medicine (e.g. [5]).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/

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

 

Tenure-Track Research Scientists Bioinformatics (m/f) [RCI Regensburg Center for Interventional Immunology]

The RCI – Regensburg Center for Interventional Immunology – is a novel biomedical research center of the University of Regensburg focusing on translational immunology in the fields of cancer immunotherapy, transplant rejection and autoimmunity. The objective of the RCI is to develop efficient immune therapeutic strategies in these areas. RCI groups are using state-of-the-art technologies (including next-generation sequencing) to investigate the mechanisms of immune regulation as well as the mechanisms underlying the complex interplay between immune and malignant cells, resulting in the control and eradication of cancer. 

We are now seeking a scientist with an academic background in bioinformatics or in a closely related discipline to support RCI groups in the analysis of high-throughput data. The position is part of the RCI Genomics team and will be associated with the Computational Core Unit of the University of Regensburg.

What we offer:

    • A 2-year position (automatically tenured after a positive evaluation in year 2) with the Regensburg Center for Interventional Immunology (RCI), where you will join a capable and dedicated team of scientists engaged in collaborative projects involving clinical and laboratory research

    • The chance to make contributions to the development of novel therapies against cancer, infections, autoimmune diseases. 

    • The freedom to co-develop inventive biostatistical approaches emerging from real-life applications

 

Your duties:

    • Software development. Developing cutting-edge software and analysis pipelines for genome data analysis

    • Data processing. Maintaining a constant flow of sequencing data 

    • Data analysis. Collaborative work with researchers whose projects profit from state-of-the-art computational methods

    • Data management. Developing databases and web infrastructure to keep track of data, analyses, and projects

    • Training and outreach. Contributing to workshops and teaching collaborating scientists how to analyze their data

 

Your profile:

    • Master/Diploma/PhD in computer science, physics, engineering, statistics, biology/bioinformatics or a related discipline

    • Sound knowledge within the field of statistics

    • Solid statistical programming skills, preferably with R, Python, or Perl

    • Ability to clearly explain methods and results to scientists of other disciplines

    • Desirable skills: Experience with the analysis of clinical or high-dimensional data, competent handling of various sequence data, good understanding of statistical methods and their application to large data sets, and knowledge of machine learning techniques, is an advantage

    • Very good written and oral communication skills in English

    • Strong interest in interdisciplinary research

 

The Regensburg Center for Interventional Immunology (RCI) is committed to increase the percentage of female scientists and encourages female applicants to apply. Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

To apply for a position please send your application documents to:

Mrs Sabine Repp 

RCI Regensburg Center for Interventional Immunology

Am BioPark 9

93053 Regensburg

Deutschland

 

Deadline for application is December 15th, 2018.

We ask for your understanding that we cannot return application documents and that

we do not accept applications submitted via email. We apologize for any inconvenience this may cause.

 

For further information please contact Prof. Dr. Michael Rehli (#49-(0)941-944-5587).

Nachwuchsgruppenleiterstelle Marburg

Am Fachbereich Mathematik und Informatik, Fachgebiet Bioinformatik, AG Prof. Dr. Dominik Heider, ist zum 01.01.2019 befristet für die Dauer von 4 Jahren, soweit keine Qualifizierungsvorzeiten anzurechnen sind, die 

drittmittelfinanzierte Stelle einer/eines Wissenschaftlichen Mitarbeiterin / Mitarbeiters als Nachwuchsgruppenleiter/in 

zu besetzen. 

Die Eingruppierung erfolgt nach Entgeltgruppe 14 des Tarifvertrages des Landes Hessen. 

Zu den Aufgaben gehören die Leitung einer Nachwuchsgruppe und die wissenschaftliche Arbeit im LOEWE Schwerpunkt MOSLA, insbesondere im AP2 (Softwarewerkzeuge, Visualisie-rung und Workflows zur Datenstrukturierung). 

Es handelt sich um eine befristet zu besetzende Qualifikationsstelle mit dem Ziel der Beruf-barkeit auf eine Professur (Habilitation oder Habilitationsäquivalenz). Im Rahmen der über-tragenen Aufgaben wird die Möglichkeit zu eigenständiger wissenschaftlicher Arbeit geboten, die der eigenen wissenschaftlichen Qualifizierung dient. Die Befristung richtet sich nach § 2 Abs. 1 Satz 2 WissZeitVG. 

Der LOEWE Schwerpunkt MOSLA soll neue Lösungsansätze zur Langzeitspeicherung von Infor-mationen in molekularbiologischen und chemischen Systemen erforschen. Damit würde das Problem des „Digital Dark Age“ gelöst werden, also die Gefahr, dass in der Zukunft Daten-träger von heute nicht mehr gelesen werden können. Neben der technischen Realisierung von Informationsspeicherung ist die spätere Dekodierung ein zentrales Thema langzeitgespeicher-ter Informationen und wird in MOSLA durch das Zusammenwirken von genetischer und chemischer Informationscodierung angegangen. 

Vorausgesetzt werden ein abgeschlossenes wissenschaftliches Hochschulstudium (Diplom, Master oder vergleichbar) im Fach (Bio-)Informatik, Data Science, Mathematik oder einem vergleichbarem Fach sowie eine Promotion in diesem Bereich. Da es sich um ein interdiszipli-näres Forschungsprojekt handelt, wird zudem Erfahrung in der Arbeit interdisziplinärer Kon-sortien erwartet. Die Nachwuchsgruppe ist mit zwei Doktorand/innen-Stellen ausgestattet; daher ist Erfahrung in der Personalführung von Vorteil. 

Wir fördern Frauen und fordern sie deshalb ausdrücklich zur Bewerbung auf. In Bereichen, in denen Frauen unterrepräsentiert sind, werden Frauen bei gleicher Eignung bevorzugt berück-sichtigt. Bewerberinnen und Bewerber mit Kindern sind willkommen – die Philipps-Universität bekennt sich zum Ziel der familienfreundlichen Hochschule. Eine Reduzierung der Arbeitszeit ist grundsätzlich möglich. Bewerberinnen/Bewerber mit Behinderung im Sinne des SGB IX (§ 2, Abs. 2, 3) werden bei gleicher Eignung bevorzugt. Bewerbungs- und Vorstellungskosten werden nicht erstattet. 

Bewerbungsunterlagen sind bis zum 09.11.2018 unter Angabe der Kennziffer fb12-0018-MOSLA-wmz-2018 bitte ausschließlich als eine PDF-Datei an Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! zu senden.