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Ph.D. Student in Translational Immunoinformatics (Diabetes)

The Institute of Computational Biology is globally recognized for innovations in data analysis and modeling of biological systems, anchored at the Helmholtz Zentrum Munich and the Technical University Munich.

For our research team "Translational Immunogenetics" we are currently looking for a

PhD Candidate for the Project: "Effects of Non-Conventional Epitopes in Type 1 Diabetes"(E13 TV-L)

Job Description

The Ph.D. project will focus on studying the effects of non-conventional epitopes on type 1 diabetes progression and their potential therapeutic exploitation.

The aims of the projects involve:

Developing bioinformatics pipelines to identify non-conventional epitopes derived from alternative splice forms, fusion proteins, and post-translational modifications

Developing predictive models to estimate the effect of post-translational modifications on HLA-epitope affinity

Investigating the prevalence and impact of non-conventional epitopes on disease progression and their interplay with the T-cell population

Developing optimization models for computer-aided vaccine design for type 1 diabetes

 

Your Qualifications

Master’s Degree in Bioinformatics, Biostatistics, Informatics or related fields (with significant experience in Bioinformatics)

Experience with NGS (transcriptomic and genomic) analysis

Experience in machine learning

Excellent programming skills (R, Python, C/C++)

Scientific curiosity and ability to work independently

Highly motivated to work in a young and multi-disciplinary, collaborative environment

Fluent in spoken and written English

 

The following qualifications are considered advantageous:

Basic understanding of the immune system

Know How in combinatorial optimization

 

Our Offer

At the Helmholtz Zentrum München, you can contribute together with leading researchers to the investigation of the development, prevention, and treatment of environmental diseases such as diabetes, chronic lung diseases, and allergies. To further promote your professional development, we offer extensive and targeted research training and career programmes. We support the reconciliation between work and private life with flexible working time models, occupational health management, day care facility for children, a childcare subsidy, Elder Care, as well as other counseling and support services.

Remuneration and benefits are following the collective agreement for the public service (EG 13 50% TV EntgO Bund). Also, there is also the possibility of granting an allowance amounting to 15% if the necessary conditions are fulfilled.

The position is (initially) limited to three years.

The activity involves specialized knowledge and experiences specific to own scientific skills.

As a holder of the Total E-Quality Award, we promote equality of opportunity. Applications from women are welcome. Qualified applicants with physical disabilities will be given preference.

Please apply through our online application system with a motivation letter, curriculum vitae, transcripts and certificates, and contact details of two academic references.

 

 Apply now: https://fragebogen.candibase.de/helmholtz/mainform.php?param=627807ce092170db5005d4c6df6be3b8&lang=en

 

(Bio-)Informatician, Natural Scientist as Projectmanager (m/f) [University Medical Center Göttingen]

The Institute for Medical Bioinformatics is looking for a

(Bio-)Informatician, Natural Scientist as Projectmanager (m/f)

The job is to be filled initially for 2 years. Remuneration is based on TV-L (up to E12). Later prolongation in form of a permanent position is desired.

About us

At the Institute for Medical Bioinformatics of the University Medical Center Göttingen, methods are being developed and applied in collaborative biomedical research projects in order to improve diagnostics and therapy decisions through molecular and genomic data.

Your tasks

    • Independent project and data management at the institute, e.g. setting-up and maintaining the necessary management systems, participation in the application for third-party funded projects, management of projects and consortia, as well as preparation of project reports.

    • Scientific interest and participation in research projects. For the job holder, there is a longer term possibility to prepare a bioinformatic dissertation.

Your profile:

    • Completed university or applied university studies (computer science, bioinformatics, engineering or natural sciences).

    • Very good English skills.

    • In-depth IT knowledge - database systems (SQL), Linux, scripting languages. 

    • Ideally, experience in project management.

    • Ideally, experience in scientific work

    • Organizational skills, good time management and independent working methods.

    • Teamwork and a high level of commitment

    • Safe and friendly manner, professionalism, discretion and loyalty combined with high resilience.

Contact for applications 

Your application should include a letter of motivation in English. Please send your application (preferably as a single PDF file) by e-mail at latest 15.01.2019 to:

 

Prof. Dr. Tim Beißbarth

University Medical Center Göttingen

Institute for Medical Bioinformatics

Goldschmidtstraße 1

37077 Göttingen

Tel.: 0551 / 39-14912

Fax: 0551 / 39-14914

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Web: http://www.bionf.med.uni-goettingen.de 

 

 

 

 

 

 

 

 

 

 

 

Wissenschaftliche Mitarbeiterin/ Wissenschaftlichen Mitarbeiter [Universität Bielefeld ]

Ihre Aufgaben
Die Arbeitsgruppe Bioinformatik und Medizinische Informatik beschäftigt sich mit der Integration und Analyse von molekularbiologischen und medizinischen Datenquellen. Ein aktueller Arbeitsbereich befasst sich mit der Entwicklung von neuartigen Methoden zur Vorhersage genetisch bedingter Interaktionen von Arzneimitteln.
Der Stelleninhaberin/dem Stelleninhaber obliegen Forschungstätigkeiten im Bereich der Informationsfusion und/oder Datenvisualisierung durchführen und darauf aufbauend biomedizinische Informationssysteme zur Analyse von Arzneimittel Interaktionen konzipieren und implementieren. Dadurch soll das existierende Forschungsprogramm (KALIS) für die Identifikation und Reduktion von Arzneimittel Interaktionen unter Berücksichtigung der molekularen Wirkmechanismen weiterentwickelt werden (75 %).
Zudem nimmt die Stelleninhaberin/der Stelleninhaber Aufgaben im Rahmen der Lehre und Betreuung von Bachelor-und Masterstudierenden wahr (25 %).

Ihr Profil
Das erwarten wir
-abgeschlossenes wissenschaftliches Hochschulstudium der Bioinformatik oder einer angrenzenden Disziplin (Masterabschluss als auch Bachelorabschluss ist möglich)
-selbstständiges, eigenverantwortliches und engagiertes Arbeiten
-ausgeprägte Organisations-und Koordinationsfähigkeit
-kooperative und teamorientierte Arbeitsweise
Das wünschen wir uns
-Erfahrungen im Bereich molekularer Wirkmechanismen und biochemischer Prozessmodellierung
-Erfahrungen im Bereich der Datenintegration und Informationsfusion

-Erfahrung bei der Betreuung von studentischen Projekt-oder Abschlussarbeiten

-Publikationstätigkeit und Erfahrungen im Bereich der Entwicklung und Implementierung webbasierter Informationssysteme

Unser Angebot
Die Vergütung erfolgt je nach persönlicher Qualifizierung bis zur Entgeltgruppe 13 des Tarifvertrages für den öffentlichen Dienst der Länder (TV-L). Die Stelle ist gemäß §2 Absatz 1 Satz 1 WissZeitVGfür die Dauer von drei Jahren befristet (entsprechend den Vorgaben des WissZeitVGund des Vertrages über gute Beschäftigungsbedingungen kann sich im Einzelfall eine abweichende Vertragslaufzeit ergeben). Die Beschäftigung ist der wissenschaftlichen Qualifizierung förderlich. Es handelt sich um eine Vollzeitstelle. Auf Wunsch ist grundsätzlich auch eine Stellenbesetzung in Teilzeit möglich, soweit nicht im Einzelfall zwingende dienstliche Gründe entgegenstehen.
Die Universität Bielefeld legt Wert auf Chancengleichheit und die Entwicklung ihrer Mitarbeiterinnen und Mitarbeiter. Sie bietet attraktive interne und externe Fortbildungen und Weiterbildungsmaßnahmen. Zudem können Sie eine Vielzahl von Gesundheits-, Beratungs-und Präventionsangeboten nutzen. Die Vereinbarkeit von Beruf und Familie hat einen hohen Stellenwert.

Interessiert?
Wir freuen uns über Ihre Bewerbung per Post an die untenstehende Anschrift oder per E-Mail unter Angabe der Kennziffer wiss18342 in einem einzigen pdf-Dokument an This email address is being protected from spambots. You need JavaScript enabled to view it. bis zum 2Wochen nach Veröffentlichung. Bitte verzichten Sie auf Bewerbungsmappen und reichen Sie ausschließlich Fotokopien ein, da die Bewerbungsunterlagen nach Abschluss des Auswahlverfahrens vernichtet werden. Weitere Informationen zur Universität Bielefeld finden Sie auf unserer Homepage unter www.uni-bielefeld.de. Bitte beachten Sie, dass Gefährdungen der Vertraulichkeit und der unbefugte Zugriff Dritter bei einer Kommunikation per unverschlüsselter E-Mail nicht ausgeschlossen werden können. Informationen zur Verarbeitung von personenbezogenen Daten finden Sie unter
http://www.uni-bielefeld.de/Universitaet/Aktuelles/Stellenausschreibungen/2018_DS-Hinweise.pdf.

Bewerbungsanschrift
Universität Bielefeld
Technische Fakultät, AG Bioinformatik/Med. Informatik
Herrn Prof. Dr. Ralf Hofestädt
Postfach 10 01 31
33501 Bielefeld
Ansprechpartner
Prof. Dr. Ralf Hofestädt
0521 This email address is being protected from spambots. You need JavaScript enabled to view it.

PhD Student position (65% E13, 3 years, available immediately) in the newly established group for Computational Systems Medicine

PhD Student position (65% E13, 3 years, available immediately) in the newly
established group for Computational Systems Medicine at the Chair of
Experimental Bioinformatics, Technical University of Munich, Freising, Germany.

Project description:
Diseases are currently defined and diagnosed based on symptoms (e.g.,
hypertension, depression) or affected organs (e.g., heart failure,
nephropathy). Clearly, there is a lack of mechanistic understanding of diseases
that could improve disease definitions and allow for more informed selection
and development of therapies. To achieve such understanding we develop
integrative bioinformatics methods leveraging network analysis, machine
learning techniques and statistical approaches. Your work will focus on the
development of graph-based machine learning techniques to identify disease- and
patient-specific dysregulated subnetworks.

What you should have:
- Degree in bioinformatics, molecular biology, computer science, or similar
- Solid understanding of molecular biology
- Experience with omics data analysis, graph theory / network biology, and machine learning
- Strong programming skills in Python, R, and / or Java
- Familiarity with Linux and HPC environments
- Fluency in written and spoken English
- Strong commitment and motivation, ability to work collaboratively

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://compsysmed.de.

Send your application including your CV, grades, publications (if any) and two
reference letters to This email address is being protected from spambots. You need JavaScript enabled to view it..

Postdoc or PhD in Statistical Bioinformatics (Pay group E13 TV-L/ 100%)

The University of Applied Sciences Koblenz offers higher education and research in the areas of mathematics, economics, technology and engineering as well as the social sciences and the arts. Our 9600 students are taught by 170 professors and more than 400 staff members at the three campuses in Koblenz, Remagen and Höhr-Grenzhausen.

The Faculty of Mathematics and Technology at the RheinAhrCampus in Remagen is currently inviting applications for the position of

Postdoc or PhD in Statistical Bioinformatics (Pay group E13 TV-L/ 100%)

in the Research Group of Professor Maik Kschischo. The post is be funded by the German Research Foundation (DFG) for a fixed-term period of 36 months within the Research Unit FOR 2800 “Chromosomal Instability: Cross-talk of DNA replication stress and mitotic dysfunction“ (see www.for2800.de). We are looking for excellent candidates with a background or strong interest in network or systems biology, statistics and machine learning, and/or cancer genomics. The goal is to develop new statistical and machine learning methods and algorithms to better understand complex and high dimensional data and to contribute statistical and computational modelling toward a biological understanding of chromosomal instability and replication stress in cancer and other diseases.

What do we have to offer?
• Excellent research opportunities
• Co-operation with leading German and international teams
• Support and supervision of your postdoc or PhD project
• The opportunity to gain a strong research track record in biomedical data sci-
ence and systems biology
• Fixed term for three years

What do we expect from you?
• A Master’s level degree in bioinformatics, statistics, mathematics, physics or computer science (PhD for Postdoc).
• Strong mathematical and statistical skills.
• Basic biological knowledge and willingness to learn new biology
• Experience with at least one programming language (e.g. R, Python or C)
• Creativity, independent thinking and passion for research
• Good English language skills

The University of Applied Sciences Koblenz strives for equal opportunities and supports the combination of job and family. Applications from women are strongly encouraged. Disabled applicants with equal qualifications and skills are preferred. We are looking forward to receiving your detailed application to be sent in one pdf file to Professor Maik Kschischo (This email address is being protected from spambots. You need JavaScript enabled to view it.) by January 6 2019. Please use the subject “FOR-2800-Postdoc” in your email.

PhD Student in Biostatistics or Bioinformatics (male/female)

The Institute for Animal Breeding and Genetics at the University of Veterinary Medicine Hannover seeks a

 

PhD Student in Biostatistics or Bioinformatics (male/female)

 

The position is available from April 1st, 2019 and limited for three years. The successful candidate will make a PhD as member of the DFG funded research training group VIPER.

 

Responsibilities will be the support of the research activities of the research group „Genomics and Bioinformatics of Infectious Diseases“. This involves the development of statistical and computation-al methods for the analysis of high-throughput sequencing data or high-throughput gene expression data (NGS, microarray data) from infection research.

 

Requirements for an application are a master’s degree in bioinformatics, statistics, molecular biology or a similar subject. Furthermore, knowledge in Linux-shell programming and in the programming envi-ronment R is expected.

 

Salary will be payed according E 13 TV-L (65%). Applications from disabled persons are welcomed.

 

 

Please send your application until 15.01.2019 via e-mail to Dr. Ann-Kathrin Haverkamp (This email address is being protected from spambots. You need JavaScript enabled to view it.) using the codeword “VIPER/BIOINFORMATICS”. Please take also note of the application guidelines provided at https://www.tiho-hannover.de/forschung/dfg-grk-viper/. Further information to the position can be given by Prof. Dr. Klaus Jung (This email address is being protected from spambots. You need JavaScript enabled to view it.), Institute for Animal Breeding and Genetics, Unversity of Veterinary Medicine Hannover.

POSTDOCTORAL RESEARCHER IN FREE ENERGY CALCULATIONS (BERLIN)

We are seeking a talented postdoctoral fellow to work at the interface of structure-informed machine learning and

alchemical free energy calculations as part of an exciting new collaboration between Prof. Dr. Andrea Volkamer and

BIH Einstein Visiting Fellow Prof. Dr. John Chodera. This project seeks to develop an integrated framework for

utilizing both state-of-the-art machine learning approaches and free energy calculations to exploit structural data,

assay data, and scalable computing resources to predict the polypharmacology of small molecule kinase inhibitors.

The postdoc will be embedded in the Volkamer group , situated within the exciting research environment of the

Charité in Berlin, and make a few extended visits to the Chodera lab at the Memorial Sloan Kettering Cancer Center

in New York City. The postdoc will be jointly supervised by Andrea Volkamer and John Chodera, with John Chodera

making several extended visits to the Charité per year under the auspices of the BIH Einstein Visiting Fellowship.

Work will focus on the development of absolute and relative alchemical free energy calculations approaches and

their integration with structure-informed machine learning approaches for predicting ligand binding affinities,

kinase polypharmacology, and the susceptibility of inhibitor binding affinities to clinical resistance mutations. The

postdoc will focus on extending our open source GPU-accelerated Python toolkits (such as openmmtools , yank , and

perses ) for protein-ligand absolute and relative alchemical free energy calculations (built on OpenMM ) and the

development of robust modeling and prediction workflows. This is an exciting opportunity to work at the

intersection of physical modeling, machine learning, and drug discovery as a stepping stone to a career in industry

or academia. Position is pending final confirmation of funding.

Starting date: 1 Feb 2019 or shortly thereafter (for up to 3 years)

Salary: TV-L E13, 100%

Desired qualifications :

● Experience with the theory and practice of small molecule alchemical free energy calculations

● Comfortable with the Python programming language

● Exposure to modern open source software development practices (GitHub, unit tests, continuous

integration)

● Good multidisciplinary team working and communication skills

Bonus qualifications:

● Experience with high-performance computing clusters and/or cloud computing

● Experience with OpenMM or machine learning frameworks such as TensorFlow

● Experience with cheminformatics, computer-aided drug discovery and/or kinase inhibition

How to apply: Interested candidates are invited to send a pre-application to This email address is being protected from spambots. You need JavaScript enabled to view it. with the

subject line “Postdoc application” that includes:

● a cover letter explaining your motivation, background, and qualifications for the position

● a detailed Curriculum Vitae (including a list of publications)

● contact information of two references

Deadline: 21 Dec 2018

see also:

https://www.charite.de/service/stellenangebot/angebot/detailinfo/dm19818b_postdocresearch_scientist/

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

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 (HIV) (E13 TV-L, 65%)

 

starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension. The position is funded by the Machine Learning Competence Center Tübingen (TUE.AI Center).

 

According to WHO about 37 million people have been living with HIV/AIDS world-wide at the end of 2017. Since there is no approved curative treatment, infected people have to take life-long anti-retroviral treatments (ART). Due to the high variability of HIV, resistant variants can emerge in patients even if they are under treatment. There are even cross-resistances between different ARTs. Therefore, there is a constant need for new targets. Highly potent and broadly neutralizing antibodies (bNAbs) have been promising candidates to fulfill this need. The goal of this Ph.D. project is to extend the work by Hake and Pfeifer to build an interpretable prediction model that can be used to give decision support for bNAbs treatment by applying and extending state-of-the-art machine learning methods.

 

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).

 

Prerequisites

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

  • Knowledge of the adaptive immune system (especially humoral immune response)

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

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

  • Databases (MySQL, NoSQL)

 

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 (HIV).

 

Application deadline: December 21st, 2018.

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

Post-doc in Biomedical Data Science (TB)

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

 

Post-doc in Biomedical Data Science (TB) (E13 TV-L, 100%)

 

starting as soon as possible. The initial fixed-term contract will be for 2 years with possible extension.

 

According to WHO there were 558,000 cases of drug-resistant tuberculosis (TB) infections world-wide in 2017 of which 82% were multidrug-resistant. In this project, which is funded through a Horizon 2020 grant by the European Commission, the successful candidate will build a prediction engine that is able to provide treatment decision support for TB-infected patients by applying and extending state-of-the-art machine learning methods. This will be in close collaboration with our Western and Eastern European partners, with a focus on multidrug-resistant strains from Eastern Europe.

 

The group has extensive knowledge at the interface between statistical machine learning, digital medicine, and computational biology. Nico 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).

 

Prerequisites

The ideal candidate will have a Ph.D. or equivalent in Biomedical Data Science, Biometry, Biostatistics, Machine Learning, Bioinformatics, Medical Informatics, Computer Science, Computational Biology or a related life science discipline. Applicants should have an interest in interdisciplinary work. Proven 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

  • Proficiency in Russian language (communication with Eastern European partners)

  • Knowledge of the adaptive immune system (especially humoral immune response)

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

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

  • Databases (MySQL, NoSQL)

 

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: Post-Doc application Biomedical Data Science (TB).

 

Application deadline: December 21st, 2018.

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

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