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Research Associate in Genome Informatics


Duties primarily include teaching and research. Research associates may also pursue independent research and further academic qualifications.
Specific Duties

The general focus of the Genome Informatics group is on developing and implementing methods for processing large sets of biological sequences and related information, like genome annotations or expression profiles. The research associate will do research on novel methods for comparing and annotating DNA and protein sequences, and apply these in a systems biology context.

Typical tasks of a research associate include writing scientific publications, and attending conferences and workshops to present the work. The position includes the responsibility to teach 4 hours/week in different interdisciplinary study programs, like the Master of Science program in Bioinformatics or the Bachelor of Science program in Computing in Science.

We are interested in a highly motivated person who is interested in working with us on cutting edge research in a pleasant working atmosphere.

A university degree in a relevant field. For example, Bioinformatics, Computational Biology or Computer Science. An academic degree like a master degree is required, a doctorate is desirable, but not conditional. Good knowledge of and experience with algorithms for processing biological sequencesis is required as well as excellent programming skills, ideally in C/C++ and Python. Knowledge of techniques from Machine Learning and/or Systems Biology is a plus. Fluent English, spoken and written, and good communication skills are mandatory. Knowledge of German is helpful; we expect the willingness to learn German for non-native German speakers.
Contact information:

Prof. Dr. Stefan Kurtz

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040 42838-7311

E13 TV-G-U, 65 % in Bioinformatics, computational systems biology

The Cluster Project ENABLE - Unraveling mechanisms driving cellular homeostasis, inflammation and infection to enable new approaches in translational medicine is a newly established interdisciplinary research network which has been initiated jointly by the Goethe-University Frankfurt, the Frankfurt Institute for Advanced Studies, the Fraunhofer Institute for Translational Medicine and Pharmacology, the Georg-Speyer-Haus and the Max Planck Institute of Biophysics. The network recently received funding from the State of Hesse and is looking to recruit

7 PhD students (m/f/d)

(E13 TV-G-U, 65 %-part-time)

as soon as possible. Positions are initially limited to three years.

There is the possibility of subsequent employment. The salary grade is based on the job characteristics of the collective agreement applicable to Goethe-University (TV-G-U).

The Cluster Project strives to unravel and understand selected pathogenic mechanisms and signaling pathways to identify disease-relevant critical targets for therapeutic intervention. The projects within the Cluster will focus on the areas of cellular homeostasis, infection and inflammation and cover the complete range from molecular mechanisms to translational clinical science and economic analysis.

ENABLE is well embedded in the excellent research infrastructure at the participating universities and research institutions; all participating sites offer access to state-of-the-art technologies, well-equipped laboratories, a vibrant scientific exchange and an internationally competitive scientific training program. Details on the available projects can be obtained from the ENABLE homepage

( and the respective group leaders.

Candidates should have a first-class academic degree in a Life Science-related discipline, informatics, computer science, mathematics or similar areas and a strong background in biochemistry, chemical biology, cell biology, molecular biology, pharmacology, bioinformatics and systems biology (bioinformatics knowledge and programming skills are

required) or biostatistics, mathematic modeling or similar.

Candidates are highly motivated and enthusiastic to join the fast-moving and internationally highly competitive field and are characterized by good collaborative skills. Very good written and spoken English is expected. As part of ENABLE, we offer tailored interdisciplinary training to all researchers in the network, a framework of common scientific activities and a strong mentorship for future career development. PhD students will be affiliated with graduate schools of the respective university and research institutions to ensure a well-structured, first-class education.

The University advocates equality between women and men and therefore urges women to apply. People with disabilities with the same qualifications are given priority.

Applicants should choose their field of interest from the projects listed below and send their application within four weeks after the publication of this advertisement in a single pdf-file including cover letter, CV, scanned academic degrees, list of publications and two references with contact details to the responsible group leader.

Please do not send any original documents as the application documents will not be returned. Travel and application costs cannot be reimbursed.

PhD projects:

Across all areas: cellular homeostasis, infection & inflammation (mathematical modeling, bioinformatics, computational systems biology) Prof. Dr. Ina Koch, Molecular Bioinformatics, Institute for Computer Science, Goethe-University Frankfurt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!

Across all areas: cellular homeostasis, infection & inflammation (mathematical modeling, bioinformatics, computational systems biology) Dr. Maria Vittoria Barbarossa, Frankfurt Institute for Advanced Studies, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! Cellular homeostasis (structural biology, systems biology, imaging) Dr. Martin Beck, Department of Molecular Sociology, Max Planck Institute of Biophysics, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! Cellular homeostasis (biochemistry, cell biology) Dr. Anja Bremm, Institute of Biochemistry II, Goethe-University Frankfurt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! Cellular homeostasis (biochemistry, cell biology, molecular biology) Prof. Stefan Müller, Institute of Biochemistry II, Goethe-University Frankfurt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! Infection (pharmacy, cell biology) Prof. Dr. Maike Windbergs, Institute of Pharmaceutical Technology and Buchmann Institute for Molecular Life Sciences, Goethe-University Frankfurt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! Tissue homeostasis & Inflammation (developmental biology, cell biology) Prof. Dr. Virginie Lecaudey, Institute for Cell Biology and Neuroscience, Goethe-University Frankfurt, Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!


Combinatorial Algorithms on Strings and Graphs

We are looking for a talented and motivated PhD student with a special interest in algorithms and data structures and their application in bioinformatics (sequence analysis). The PhD student will be positioned at CWI within the "Algorithms for PAngenome" (ALPACA) network

( funded by the European Commission through the Horizon 2020 Marie Sklodowska-Curie ITN Programme.

The move from sequence- to graph-based pan-genome data structures is unavoidable when seeking to exploit the wealth of genome data, instead of having devices massively congested. Putting the paradigm shift (from sequences to graphs) in effect requires new ways of thinking about genomes, as well as computer programs and mathematical models that reflect this. However, developing, maintaining and computationally exploiting graph-based pan-genomes requires skills that common-day education does not yet provide. The goal of ALPACA is to train a new class of researchers who are able to deal with the masses of genome data in terms of the progressive, graph-based approaches the research of this project deals with.


Objectives: Comparing pan-genomes amounts to comparing two graphs, generalizing the idea to align two genomes. We aim at developing algorithms for 'whole-pan-genome alignment'. Though for aligning two networks approaches already exist, they do not address the peculiarities of pan-genome graphs, in, for example, de Bruijn graph or variation graph based pan-genomic data structures. We will address these particular issues in full detail.


 Supervised by: Solon P. Pissis (


Co-supervised by: Leen Stougie (



Candidates are required to have a Master’s degree in Computer Science, Mathematics or a related discipline, and a specialization in Algorithms, Combinatorics, Combinatorial Optimization or related fields. Preferable qualifications for candidates include proven research talent in a Master’s project, an excellent command of English, and good academic writing and presentation skills.


On the starting date of their employment with CWI, candidates must be in the first four years of their research career and have not (yet) been awarded a doctoral degree. Candidates also must not have resided and/nor have had their main activity (study, work, etc.) in the Netherlands for more than 12 months during the 3 years prior to the starting date of their employment with CWI.


More details and application instructions can be found here:


Application deadline: April 30, 2021

Bioinformatician [DKFZ, Division of Personalized Medical Oncology]

The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 3,000 employees, we operate an extensive scientific program in the field of cancer research.


The Division of Personalized Medical Oncology (Director: Prof. Dr. Dr. Sonja Loges) focusses on the identification of novel cancer-promoting mechanisms in the tumor microenvironment. Based on these functional insights we aim to derive novel targets for therapeutic intervention. Translation of research findings into the clinic will be possible at the newly founded „DKFZ-Hector Cancer Institute at the University Hospital Mannheim“, which is also directed by Prof. Sonja Loges and generously funded by the Hector Foundation II.


Job description:


Together with the Division of Applied Bioinformatics (Director: Prof. Dr. Benedikt Brors) we are looking for an enthusiastic individual to develop methods for integrative analysis of multi­level data on tumors, including whole-genome and/or whole-exome sequences of tumor and germline genomes, single-cell and spatial transcriptomics data, methylomes and corresponding clinical data. The position is placed in a dynamic and multinational, multidisciplinary team which works closely with national as well as international collaboration partners in academics as well as pharmaceutical companies. The workplace is located in Heidelberg.




The applicant should hold at least a master's degree in bioinformatics, computational biology or related fields, or a degree in biological sciences with demonstrated experience in computational biology / bioinformatics.


Previous experience in developing and applying computational methods applied to large datasets is expected. We especially seek candidates with prior experience in the analysis and the management of NGS data in the field of cancer biology.


Proficiency with relevant scripting languages and statistical data analysis tools such as Python and R (or equivalent) is required. Single-cell experience is a plus.


The ideal applicant should have demonstrated the ability to work independently and creatively. You 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 other partners.


Full applications should include a curriculum vitae including any potential publications, a letter of motivation, certificates, expected availability date, and 2-3 references.


We offer:


  • Interesting, versatile workplace
  • International, attractive working environment
  • Campus with modern state-of-the-art infrastructure
  • Salary according to TV-L including social benefits
  • Possibility to work part-time
  • Flexible working hours
  • Comprehensive further training program


Earliest Possible Start Date: as soon as possible


Duration: The position is limited to 2 years with the possibility of prolongation.


The position can in principle be part-time.


Application Deadline: 17.04.2021




Dr. Melanie Janning
Phone +49 (0)621/383-1757


Please note that we do not accept applications submitted via email. 




Professur (W 2) für Strukturelle Bioinformatik

In der Fakultät für Biologie und Vorklinische Medizin ist am Regensburg Center for Biochemistry eine Professur der Besoldungsgruppe W 2 für Strukturelle Bioinformatik im Beamtenverhältnis auf Lebenszeit zum nächstmöglichen Zeitpunkt zu besetzen. Die Professur soll den Schwerpunkt der Fakultät und des Regensburg Center for Biochemistry im Bereich der Strukturbiologie durch die bioinformatische Analyse zellulärer Makromoleküle ergänzen. Zudem ist eine Stärkung der bestehenden Sonderforschungsbereiche der Fakultät erwünscht, insbesondere des SFB 960. Die Ausschreibung richtet sich an hoch qualifizierte Persönlichkeiten, die durch exzellente Publikationsleistungen und Drittmitteleinwerbungen ausgewiesen sind. In der Lehre ist das Fachgebiet Bioinformatik im Rahmen der Bachelor- und Masterstudiengänge Biologie und Biochemie zu vertreten. Einstellungsvoraussetzungen sind neben den allgemeinen dienstrechtlichen Voraussetzungen ein abgeschlossenes Hochschulstudium, pädagogische Eignu
ng, besondere Befähigung zu wissenschaftlicher Arbeit, die in der Regel durch die Qualität einer Promotion nachgewiesen wird, sowie zusätzliche wissenschaftliche Leistungen, die durch eine Habilitation oder gleichwertige wissenschaftliche Leistungen, die auch außerhalb des Hochschulbereichs erbracht sein können, nachgewiesen oder im Rahmen einer Juniorprofessur erbracht werden. Die Vereinbarkeit von Familie und Beruf ist der Universität Regensburg ein besonderes Anliegen (nähere Infos unter Um den Gleichstellungsauftrag zu erfüllen und die Zahl ihrer Professorinnen zu erhöhen, fordert sie qualifizierte Wissenschaftlerinnen ausdrücklich zur Bewerbung auf. Schwerbehinderte werden bei im Wesentlichen gleicher Eignung bevorzugt berücksichtigt. Die beamtenrechtlichen Voraussetzungen für eine Ernennung richten sich nach den Bestimmungen des BayBG und des BayHSchPG. Die Altersgrenze des Art. 10 Abs. 3 BayHSchPG ist zu beachten. Bewerbungen 
mit den üblichen Unterlagen (Lebenslauf, Zeugnisse, Urkunden, Schriftenverzeichnis mit den wichtigsten Sonderdrucken, Forschungsplan, Lehrkonzept) sind elektronisch bis zum 3. Mai 2021 an den Dekan der Fakultät für Biologie und Vorklinische Medizin (Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!) der Universität Regensburg, D-93040 Regensburg, zu richten. Hinweise zum Datenschutz finden Sie unter

W1-Professur für Biomedizinische Informatik

Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Die Medizinische Fakultät besetzt am Institut für Medizininformatik, Biometrie und Epidemiologie zum frühestmöglichen Zeitpunkt eine

W1-Professur für Biomedizinische Informatik
im Beamtenverhältnis auf Zeit zunächst für die Dauer von drei Jahren. Nach positiver Evaluierung ist eine Verlängerung auf insgesamt sechs Jahre vorgesehen.

Zu den Aufgaben gehört, das Fachgebiet in Forschung und Lehre angemessen zu vertreten. Die Professur ist dabei insbesondere in das MIRACUM-Projekt eingebunden, in dem zehn Universitätsklinika, zwei Hochschulen und ein Industriepartner mit dem Ziel vereint sind, klinische Daten, Bilddaten und Daten aus molekularbiologischen und genomischen Untersuchungen über modular aufgebaute, skalierbare und föderierte Datenintegrationszentren für innovative Forschungsprojekte nutzbar zu machen. Die Bewerber (m/w/d) sollen über einen bioinformatischen Hintergrund und Erfahrungen im medizinischen Forschungsdatenmanagement (FAIR-Prinzipien) verfügen, um Aspekte des Data Engeneering und der Data Integration im medizinischen Kontext in eigenständiger Forschung weiterzuentwickeln. Von Vorteil sind Erfahrungen in der Kooperation mit klinischen und präklinischen Arbeitsgruppen, in der internationalen Forschungskooperation sowie im Projekt- und Teammanagement. Erwartet werden eine Mitarbeit in den Forschungsverbünden der FAU und des Universitätsklinikums Erlangen (z.B. Sonderforschungsbereiche, Graduiertenkollegs, Interdisziplinäres Zentrum für Klinische Forschung, Spitzencluster Medical Valley, Graduate School in Advanced Optical Technologies [SAOT]) und eine Zusammenarbeit mit dem im Aufbau befindlichen Department Artificial Intelligence in Biomedical Engineering (AIBE) an der FAU. An der Medizinischen Fakultät bestehen unter anderem die Studiengänge Humanmedizin, Zahnmedizin, Molekulare Medizin, Medical Process Management und Integrated Immunology. Eine Mitwirkung in der vorwiegend in deutscher Sprache zu erbringenden Lehre, insbesondere in Vorlesungen in den Studiengängen Humanmedizin und Informatik (Nebenfach Medizinische Informatik), wird erwartet.

Einstellungsvoraussetzungen sind ein abgeschlossenes Hochschulstudium, pädagogische Eignung, besondere Befähigung zu wissenschaftlicher Arbeit, die in der Regel durch die herausragende Qualifikation einer Promotion nachgewiesen wird. Sofern vor oder nach der Promotion eine Beschäftigung als wissenschaftlicher Mitarbeiter oder wissenschaftliche Mitarbeiterin oder als wissenschaftliche Hilfskraft erfolgt ist, sollen Promotions- und Beschäftigungsphase zusammen nicht mehr als sechs Jahre (bei Medizinern: nicht mehr als neun Jahre) betragen haben. Fristverlängernd wirken sich u.a. Mutterschutz und die Inanspruchnahme von Elternzeit aus.

Die FAU erwartet die Teilnahme an der akademischen Selbstverwaltung, das Engagement zur Einwerbung von Drittmitteln und eine hohe Präsenz an der Universität zur intensiven Betreuung der Studierenden. Die Bereitschaft zur englischsprachigen Lehre wird gewünscht.

An der FAU werden W1-Professuren durch ein Mentorat unterstützt, zudem erhalten sie eine sächliche Erstausstattung. Das Förderinstrument der Leistungsvereinbarung sichert die faire und transparente Evaluierung.

Die FAU verfolgt eine Politik der Chancengleichheit unter Ausschluss jeder Form von Diskriminierung. Bewerbungen von Schwerbehinderten werden bei ansonsten im Wesentlichen gleicher Eignung, Befähigung und fachlicher Leistung bevorzugt berücksichtigt. Bewerbungen von Wissenschaftlerinnen werden ausdrücklich begrüßt. Die FAU ist Mitglied im Verein Familie in der Hochschule e.V. und bietet Unterstützung für Dual-Career-Paare an.

Bewerbungen sind mit den üblichen Unterlagen (CV, Schriftenverzeichnis, Lehrerfahrung, Drittmitteleinwerbungen, Zeugnisse und Urkunden) webbasiert unter bis zum 23.04.2021 erwünscht, adressiert an den Dekan der Medizinischen Fakultät. Für Fragen und weitere Informationen steht der Dekan unter Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! sehr gerne zur Verfügung.




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W1 Professorship for Biomedical Informatics

The Faculty of Medicine at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for a
W1 Professorship for Biomedical Informatics (Assistant Professor)
at the Institute of Medical Informatics, Biometry, and Epidemiology. The professorship is to be filled by the earliest possible starting date for an initial period of three years. Upon successful evaluation, the appointment will be extended for another three years. 
We seek to appoint a top early career scientist who will develop outstanding expertise in the field. The professorship is involved in the MIRACUM project, which unites ten university hospitals, two universities and a partner from the healthcare industry, with the aim of making clinical, image, molecular and genomic data available for use in innovative research projects via modular, scalable and federated data integration centres. Candidates should come from a biomedical informatics background and have experience in medical research data management (FAIR principles) to develop aspects of data engineering and data integration in a medical context in their own research. Experience of collaboration with clinical and pre-clinical working groups, international research and project and team management is an advantage. The successful candidate is expected to become actively involved in research networks at FAU and the Faculty of Medicine (Collaborative Research Centres, Research Training Groups, Interdisciplinary Centre for Clinical Research, leading-edge cluster Medical Valley, Graduate School in Advanced Optical Technologies [SAOT]) and collaborate with the Department of Artificial Intelligence in Biomedical Engineering (AIBE) at FAU, which is currently being established. The Faculty of Medicine offers degree programmes in medicine, dentistry, molecular medicine, medical process management and integrated immunology. The assistant professor will be expected to participate in teaching, which is mostly carried out in German, particularly in lectures for medicine and computer science (medical informatics as a minor subject).
Successful candidates demonstrate initial academic achievements and the capacity for independent research at the highest international standards. You have substantial research experience abroad and/or experience in managing research projects and in raising third-party funding. A university degree and an outstanding doctoral degree as well as a passion for education and pertinent teaching experience are also prerequisites. Candidates who are able and willing to teach in both English and German are desired.
FAU expects applicants to become actively involved in administering academic affairs and in developing strategic initiatives. FAU pursues a policy of intense student mentoring and therefore expects its teaching staff to be present during lecture periods.
FAU offers career development, mentoring and an attractive initial research budget. Based on international standards and transparent performance agreements, FAU ensures a fair evaluation process.
In its pursuit of academic excellence, FAU is committed to equality of opportunity and to a proactive and inclusive approach, which supports and encourages all under-represented groups, promotes an inclusive culture and values diversity. FAU is a family-friendly employer and is also responsive to the needs of dual career couples.
Please submit your complete application documents (CV, list of publications, list of lectures and courses taught, copies of certificates and degrees, list of third-party funding) online at by 23. April 2021, addressed to the Dean of the Faculty of Medicine. Please contact Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein! with any questions.): Titel: Text:

PhD student in precision cancer bioinformatics

Ref. no.: BIH-42.21


The Digital Health Center, headed by Prof. Roland Eils, develops and applies state-of-the-art and innovative technologies to healthcare research with a strong focus on machine learning, bioinformatics, imaging and genomics. The department has a strong standing within international consortium (e.g. Human Cell Atlas, ICGC, de.NBI, ELIXIR, EOSC), and have exceptional computational resources (in-house HPC, cloud, Nvidia DGX and FPGA technology).


We have recently established a precision medicine genomics platform, which aims to use whole genome and transcriptome sequencing for cancer patients. Building on top of an excellent existing pipeline, we aim to further develop the computational analytics part of the pipeline in the upcoming years.


Your area of responsibility:


- Undertake and publish excellent scientific research

- Interacting with other members of the clinical genomics program including management, pathology, genomics and clinical partners

- Analyzing genome sequencing data for prospective patients, working closely with clinicians to identify actionable mutations

- Analyzing genome sequencing data for retrospective studies

- Development of new genomics workflows (e.g. supporting new genome references and genomics lesions such as STRs and enhancer hijacking) and interacting with our Data Management Platform team for deployment in a production environment

- Development and implementation of novel computational methods that aid genomics based diagnostics and prognosis

- Interacting with other collaborative sites, in particular the DKFZ and NCT in Heidelberg


Your profile:


- A PhD candidate with a recent masters degree in bioinformatics, cancer genomics, computer science, medicine, physics or similar

- Ambitious, self-driven, a thirst for answering scientific questions and aim to build a scientific career in biomedical data science research

- Excellent programming proficiency especially in Python, R, Julia, bash or similar

- Experience in designing and implementing data analysis pipelines

- Experience with next generation sequencing data processing and analysis

- Experience with linux based HPC or cloud environments

- Fluent in English (written and spoken)


Qualifications – desirable:


- Prior research experience in liquid biopsies, cancer genomics data, single cell ‘omics data, or spatial transcriptomics

- Knowledge of transcriptional regulation and epigenomics

- Knowledge of cancer immunology

- Experience with machine learning methods (e. g. RF, NMF, VAE) and frameworks (e. g. PyTorch, TensorFlow, Keras, sklearn)

- Experience with workflow management systems and similar paradigs (e. g. ELIXIR-WES, snakemake, NextFlow)


Start: Immediately


Length of employment: 3 years


Working time: 25,35 hrs./week


Pay scale: E13 acc. to collective agreement TVöD VKA – K


Contact person: For further information please contact Dr. Naveed Ishaque, E-Mail: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!

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