July 2019 - BBClist - maillist.psb.ugent.be

Upcoming Training Sessions
by ELIXIR Belgium 25 Jul '19

25 Jul '19

ELIXIR Belgium's training calendar Fall 2019! No Images? Click here https://email.vibconferences.be/t/r-e-jiuludtd-uhtudkhjjk-n/ Training Events - Fall 2019 Train the Trainer This course aims to improve your teaching skills and is made up of four sessions: Learning principles and how they apply to trainingTraining techniques to enhance learner engagement and participationAssessment and feedback in trainingSession, course, and materials design Date: 29 & 30 August Location: Hogeschoollaan 1, Breda Trainers: Patricia Palagi (SIB Swiss Institute of Bioinformatics) & Mateusz Kuzak (Dutch Techcentre for Life Sciences) Info & registration [https://www.eventbrite.co.uk/e/elixir-excelerate-train-the-trainer-event-ti…] Protein Properties Prediction In this workshop, we address how to predict features of proteins from their sequence only, using Python scripts to access APIs of web services available online. We will introduce single-sequence based predictions of biophysical characteristics of proteins, methods that use multiple sequence alignments, and methods that determine the difference between a protein and its mutant form. Date: 10 September Location: U-Residence, Brussels Trainers: Wim Vranken & Niloofar Shirvanizadeh Info & registration [https://training.vib.be/bioinformatics-tools-predict-protein-properties-seq…] Galaxy Training: Using Galaxy for RNA-seq This practical aims to familiarize you with the Galaxy user interface & execute a complete analysis of RNA-seq data. It will teach you how to perform basic tasks such as importing data, running tools, working with histories, creating workflows, and sharing your work. You'll also learn how to perform filtering and quality control of reads, mapping to reference genomes and variant calling. Date: 8 October Location: Clemenspoort, Gent Trainers: Lieven Sterck & Tuur Muyldermans Info & registration [https://training.vib.be/galaxy-training-using-galaxy-rna-seq] Functional Plant Bioinformatics (PLAZA) This two-day workshop will introduce the basic concepts of comparative and functional -omics data analysis in plants through lectures and practical hands-on sessions. You will have a good understanding of the organization of plant genomes, the evolution of plant gene families, the different systems used to describe gene functions and extract relevant biological information from -omics gene sets. Date: 21 & 22 October Location: UGent-VIB Research Building FSVM, Gent Trainers: Klaas Vandepoele & Michiel Van Bel Info & registration [https://training.vib.be/functional-plant-bioinformatics-plaza] ELIXIR Belgium on behalf of VIB You receive this email because you work at VIB or you have expressed interest in our Bioinformatics training sessions. Feel free to forward this email to interested colleagues. If you do not want to receive this email anymore, you can unsubscribe here below. Preferences https://bits.updatemyprofile.com/r-jiuludtd-DCA2A3C5-uhtudkhjjk-p | Unsubscribe https://email.vibconferences.be/t/r-u-jiuludtd-uhtudkhjjk-x/

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COMPUTATIONAL BIOLOGIST - TUMOR IMMUNOLOGY
by Lodewyk Wessels 25 Jul '19

25 Jul '19

VACANCY COMPUTATIONAL BIOLOGIST - TUMOR IMMUNOLOGY YOUR ROLE WITHIN THE INSTITUTE The research groups of Dr Karin de Visser, dr Marleen Kok and Prof dr Lodewyk Wessels, are looking for a motivated and talented Computational Biologist to join their teams at the Netherlands Cancer Institute (NKI). The Inflammation and Cancer group of dr. Karin de Visser is studying the impact of the immune system on metastatic breast cancer utilizing sophisticated mouse tumor models and state-of-the art ex vivo and in vitro immunological and molecular assays. The lab of de Visser closely collaborates with the translational research group of medical oncologist dr Marleen Kok. The mission of this team is to discover novel mechanisms underlying the crosstalk between breast cancer and the immune system, to optimize immunotherapy for breast cancer patients using novel combination treatments in clinical trials and the discovery of predictive biomarkers. The Computational cancer biology group of Prof dr Lodewyk Wessels is focused on quantifying and understanding treatment response in model systems and patients. To this end we develop bespoke and novel computational methods focusing on data integration and tailored to new technologies. We actively collaborate with many research groups in the NKI and strongly believe in the power of 'team science'. PROJECTS You will be involved in the following projects: 1. MOUSE MODELS FOR METASTATIC ESCAPE FROM IMMUNE CONTROL. To study the causal relationship between immune cells and metastatic breast cancer, we utilize state-of-the art genetically engineered mouse tumor models. We have extensive RNA-sequencing datasets of isolated immune cell populations, as well as RNA-sequencing and exome sequencing data of primary breast tumors and organ-specific metastases from these mouse models. You will be responsible for the computational analyses of the data, and to extract candidate pathways/genes from these datasets that can subsequently be tested in follow up experiments in the lab. Moreover, you will link these pre-clinical data to human datasets. 2. SYSTEMIC AND INTRA-TUMORAL IMMUNOMONITORING FOR PRECISION IMMUNE-MODULATION. We are performing extensive immunomonitoring studies in human breast cancer patients treated with immune checkpoint blockade, with the ultimate aim to validate hypotheses derived from our preclinical research in human cancer patients, and to stratify breast cancer patients for immunomodulatory therapies. We are setting-up multiplex immunohistochemistry with antibody panels that audit intratumoral lymphoid and myeloid cell populations and their functional state. In parallel, we have established an extensive multiplex flow cytometry pipeline to monitor the systemic immune landscape of breast cancer patients and healthy controls. These analyses generate a substantial amount of data which require thorough computational analyses. 3. MAPPING IMMUNO-GENOMIC INTERACTIONS. We are interested in dissecting the impact of the genetic make-up of breast tumors on the intra-tumoral and systemic immune landscape. You will be responsible for the identification and validation of genotype-immunophenotype associations by connecting DNA exome sequencing data, RNA sequencing data and immune profiles derived from our mouse tumor models and cancer patients. You will use both publicly available datasets and newly generated datasets. You will be embedded in the collaborative and enthusiastic international research groups of dr. Karin de Visser, dr Marleen Kok and Prof. dr. Lodewyk Wessels, providing a unique environment that combines computational cancer biology with pre-clinical and translational research into immune-oncology. YOUR PROFILE We seek to recruit an ambitious postdoc, capable of independent thinking, with a strong commitment to translational research. Candidates should hold a degree in bioinformatics, computer science or a related discipline, have experience in statistics and/or machine learning and be proficient in bioinformatics programming languages (e.g. R, Python). We expect candidates to be highly self-motivated, creative, and a team-player with strong communication skills. General background knowledge in biology and immunology is essential, and experience with projects involving the use of genomics and immune profiling data to identifying candidate targets and biomarkers is a plus. WANT MORE INFORMATION? Please visit our home pages https://www.nki.nl/divisions/tumor-biology-immunology/de-visser-k-group/ https://ccb.nki.nl or contact Karin de Visser: k.d.visser(a)nki.nl Marleen Kok: m.kok(a)nki.nl Lodewyk Wessels: l.wessels(a)nki.nl

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Postdoctoral position in computational biology and bioinformatics
by Marianne Rooman 22 Jul '19

22 Jul '19

Postdoctoral position in computational biology and bioinformatics The Computational Biology and Bioinformatics group (3BIO-BioInfo) of the Brussels University (ULB) is seeking candidates for a postdoctoral position. Research context: Maintaining the stability and interactions of structured proteins is a necessary condition for them to function properly. Designing variants with optimized stability or affinity is a way to create new functional proteins that are stable in various conditions, even outside their physiological range. On the other hand, interpreting the molecular effect of genetic variants is a fundamental step in understanding the pathogenesis processes and a prerequisite to set up personalized drugs and therapies. Considering that experimental techniques are slow and costly, the challenging development of efficient bioinformatics tools, capable of predicting the change in protein stability and interactions upon mutations, could guide and limit the experiments that must be performed to identify relevant mutants. Such tools, usually based on combinations of physics-based and machine-learning approaches, possess a large series of applications in the biotechnological sectors from food to biofuel industry, as well as in the biomedical sector focused on genetic diseases. They also present a fundamental interest as they shed some light on the relationship between protein sequence, structure and function, a longstanding problem in protein science, as well as on the genotype-phenotype relationship. Furthermore, understanding how natural evolution guided protein mutations and led from ancient to current proteins, and what exactly drives this evolution, is another motivating issue. Although stability and natural evolution are obviously linked, their exact relation is complex and far from known. Objective: Design, develop and apply dedicated software for predicting and gaining understanding of protein stability and interactions, of disease-causing variants, and/or of evolutionary pressure. Offer: A full time postdoctoral position for 12 months starting between September and December 2019, financed by the FNRS Fund for Scientific Research, with the possibility of extension through an FNRS postdoctoral research grant or a Marie Curie EC grant. Required: - PhD degree in Sciences (Bioinformatics, Bioengineer, Physics, Chemistry, Informatics). - Excellent programming and computer science skills. - Excellent communication skills in English. - Excellent publication record. Desirable: - Experience in the area of protein structural bioinformatics, physics-based approaches and machine learning. Contact: Please submit to Marianne Rooman (mrooman(a)ulb.ac.be <mailto:mrooman@ulb.ac.be>): (1) a cover letter detailing your background and interest in the position, (2) a full CV and (3) two references (with name, email, address, phone number). Application deadline: Please submit your application by September 15, 2019.

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ELIXIR Train-the-Trainer event in Breda, the Netherlands, 29-30 August 2019, registration open.
by Celia van Gelder 21 Jul '19

21 Jul '19

Dear all, ELIXIR-NL and ELIXIR-CH are pleased to announce an ELIXIR Train the Trainer course. It will take place on 29-30 of August in Breda. The registration for the event is free of charge. Train-the-Trainer courses are for scientists: * with some to little or no teaching experience, * who want to become a teacher or a better one, and * who believe teaching is - or may become - a relevant aspect of their professional development. The course is made up of four sessions, covering * Learning principles and how they apply to training * Training techniques that can be used to enhance learner engagement and participation * Assessment and feedback in training * Session, course, and materials design The workshop format is very interactive and hands-on. The registration and agenda with more details available here <https://www.eventbrite.co.uk/e/elixir-excelerate-train-the-trainer-event-ti…> . For ELIXIR members there is a Travel Grant Schema in place. Please check here <https://elixir-europe.org/intranet/travel-grant-scheme> for more details (ELIXIR Intranet login needed). The deadline for the applications for the Travel Grant is 30 days before the start of the event. Please feel free to contact mateusz.kuzak(a)dtls.nl <mailto:mateusz.kuzak@dtls.nl> or celia.van.gelder(a)dtls.nl <mailto:celia.van.gelder@dtls.nl> with any questions. Dr. Celia W.G. van Gelder Programme Manager DTL Learning Training Coordinator ELIXIR-NL ELIXIR Training Platform Leader tel. +31613375327 e-mail: celia.van.gelder(a)dtls.nl <mailto:celia.van.gelder@dtls.nl> websites: https://www.dtls.nl/, https://www.elixir-europe.org/platforms/training skype: celia.van.gelder Office: DTL | Jaarbeurs Innovation Mile (JIM) | 6th floor Beatrixgebouw | Jaarbeursplein 6 | 3521 AL Utrecht Postal address: Postbus 8500 | 3503 RM Utrecht While I may be sending this email outside my normal office hours, I have no expectation to receive a reply outside yours.

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BSC: Researcher in Artificial Intelligence applied to life sciences (RRE)
by BSC RRHH 19 Jul '19

19 Jul '19

Researcher in Artificial Intelligence applied to life sciences (RRE) *Reference:*173_LS_AI_RRE *Context And Mission* The Life Sciences Department at the BSC integrates the independent research of senior scientists that work on various aspects of computational biology, ranging from bioinformatics for genomics to computational biochemistry and text mining. The Computational Biology group is involved in multiple projects in collaboration with experimental groups generating state-of-the-art genomics and epigenomics datasets, actively participating in the International Human Epigenome Consortium and with the general aim of enabling new approaches in personalized medicine. Current efforts involve integration of different types of omics data, with a particular emphasis on epigenomics. We are establishing methods to study genome architecture exploiting interdisciplinary tools such as machine learning and network theory. The mission of the Computer Science Department at the BSC is to influence the way machines are built, programmed and used: computer and system architecture, programming models and performance tools, resource management, Big Data and artificial intelligence. The HPAI (High Performance Artificial Intelligence) research group is part of the Computer Science department, and it performs research in Artificial Intelligence, focused on the solutions, problems and infrastructure provided by High Performance Computing. The group actively collaborates with researchers from other fields, with the goal of applying machine learning to challenging problems in a wide variety of domains. HPAI has active collaborations with several large tech companies, pursuing lines of research of common interest. The group is also involved in multiple research projects, both European and national. Although the HPAI is open to all aspects of AI, currently its main lines of research are deep neural networks and graph analytics. The post holder will collaborate with the Life Sciences department and the HPAI research group in the Computer Science department, with the goal of finding AI solutions to life sciences challenges. This will include working closely with researchers from both areas, programming, testing and dissemination of the research. The candidate will be able to develop an independent research programme within the broad topics mentioned above. The Researcher will work in a highly sophisticated HPC environment, will have access to state-of-the-art systems and computational infrastructures, and will establish collaborations with experts in different areas both at the local and international levels. *Key Duties* * Development of AI solutions, with special emphasis on machine learning methods, for the analysis and interpretation of biological data * Use predictive computational methods based on statistical and inference approaches to model complex biological processes * Integration of heterogeneous data sources using advanced data mining techniques MORE INFO & APPLY HERE:https://www.bsc.es/join-us/job-opportunities/173lsairre <https://www.bsc.es/join-us/job-opportunities/173lsairre> http://bsc.es/disclaimer

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PhD student position in machine learning / cancer biology
by Patrick Deelen 17 Jul '19

17 Jul '19

https://www.umcg.nl/NL/UMCG/Werken_in_het_UMCG/Vacatures/Externe_vacatures/…

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The Swedish Elixir node is looking for a Data Steward
by Bengt Persson 15 Jul '19

15 Jul '19

Dear all, The Swedish Elixir node is looking for a Data Steward. Deadline is 10 September. More details are available at: https://www.uu.se/en/about-uu/join-us/details/?positionId=277048 All the best, Yours, Bengt Persson Head of Node Elixir-SE -- Bengt Persson, M.D., Ph.D. Professor of Bioinformatics Director of NBIS (National Bioinformatics Infrastructure Sweden) Science for Life Laboratory Uppsala University & Karolinska Institutet Telephone: +46 18 471 4422 Mobile phone: +46 70 425 0230 Facsimile: +46 18 530 396 E-mail: bpn(a)icm.uu.se, bpn(a)nbis.se, bengt.persson(a)ki.se Addresses: Uppsala University | Karolinska Institutet SciLifeLab | SciLifeLab ICM -- Department of | MBB -- Department of Medical Cell and Molecular Biology | Biochemistry and Biophysics BMC, room C10:308c | House Gamma, level 6, G6613 Box 596 | Box 1031 S-751 24 Uppsala, SWEDEN | S-171 21 Stockholm, SWEDEN När du har kontakt med oss på Uppsala universitet med e-post så innebär det att vi behandlar dina personuppgifter. För att läsa mer om hur vi gör det kan du läsa här: http://www.uu.se/om-uu/dataskydd-personuppgifter/ E-mailing Uppsala University means that we will process your personal data. For more information on how this is performed, please read here: http://www.uu.se/en/about-uu/data-protection-policy

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PhD position in population genetics in Coffea at ILVO (Belgium)
by Tom Ruttink 15 Jul '19

15 Jul '19

Dear, We currently have a PhD position in population genetics in Coffea open and are looking for suitable candidates. Could you please spread the announcement in your network? more information can be found on our website: https://www.ilvo.vlaanderen.be/language/en-US/EN/Work-at-ILVO/PhD-coffee.as… thank you in advance, kind regards, Tom Ruttink Senior Scientist Genomics ILVO Instituut voor Landbouw-, Visserij- en Voedingsonderzoek Flanders research Institute for Agriculture, Fisheries and Food Eenheid Plant | Plant Sciences Unit Caritasstraat 39 9090 Melle (Belgium) T +32 9 272 28 78 tom.ruttink(a)ilvo.vlaanderen.be<mailto:tom.ruttink@ilvo.vlaanderen.be> www.ilvo.vlaanderen.be<http://www.ilvo.vlaanderen.be/> www.ilvogenomics.be<http://www.ilvogenomics.be/> [http://intranet.ilvo/Portals/0/images/Communicatie/Huisstijl/Twitter.jpg]<https://twitter.com/ILVOvlaanderen> [http://intranet.ilvo/Portals/0/images/Communicatie/Huisstijl/FB.jpg?ver=201…] <http://www.facebook.com/instituutvoorlandbouwenvisserijonderzoek> [http://intranet.ilvo/Portals/0/images/Communicatie/Huisstijl/LinkedIn.jpg] <https://www.linkedin.com/company/ilvo> /////////////////////////////////////////////// [http://intranet.ilvo/Portals/0/images/Communicatie/Huisstijl/Leeuw.jpg]

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Okinawa workshop on Qualitative Computational Modeling for Biological Networks
by Yves Moreau 12 Jul '19

12 Jul '19

Dear colleagues, It's our pleasure to invite you to Okinawa for a workshop on Qualitative computational modeling for biological networks. The workshop will be held on October 31st, as a satellite to the 2019 ICSB conference: https://www2.aeplan.co.jp/icsb2019/tutorials_satellite.html <https://www2.aeplan.co.jp/icsb2019/tutorials_satellite.html> The program will cover: • Boolean and logical modeling • Petri nets • molecular interaction maps • community standards development and interoperability • model composition and modularity • analytical methods • network inference • model curation and annotation And we can already announce invited talks by: • Marcelle Kaufman (Free University of Brussels, Belgium) • Edda Klipp (Humboldt University, Berlin, Germany) • Takeyuki Tamura (Institute for Chemical Research, Kyoto University, Kyoto, Japan) Applications are now open for oral presentation based on abstract submission. Call for oral presentations: https://www.easychair.org/cfp/QualMod2019 <https://www.easychair.org/cfp/QualMod2019> Submission link: https://easychair.org/my/conference?conf=qualmod2019 <https://easychair.org/my/conference?conf=qualmod2019> Submissions will be selected after review by the workshop's scientific commitee. Scientific committee: • Tatsuya Akutsu (Institute for Chemical Research, Kyoto University, Kyoto, Japan) • Réka Albert (Pennsylvania State University, Pennsylvania) • Claudine Chaouiya (Aix-Marseille University, France / Gulbenkian Institute, Portugal) • Thomas Helikar (Department of Biochemistry, University of Nebraska, USA) • Ina Koch (Institute of Computer Science, Goethe University, Frankfurt, Germany) • Reinhard Laubenbacher (Jackson Laboratory / UConn School of Medicine, Connecticut) • Hiroshi Matsuno (Yamaguchi University, Japan) • Atsushi Mochizuki (Kyoto University, Japan) • Heike Siebert (Berlin Free University, Germany) Key dates: • Submission deadline: July 13th • Notification of Acceptance: July. 31st Workshop registration: As a satellite to ICSB we don't have a separate registration process. All participants must be registered to the main event. • Early bird registration until June 28th. • Late registration till September 20th https://www2.aeplan.co.jp/icsb2019/registration.html <https://www2.aeplan.co.jp/icsb2019/registration.html> Looking forward to meeting you in Okinawa, Adrien Fauré & Denis Thieffry. -------------------------------------------------- Prof. Denis THIEFFRY Ecole Normale Supérieure - Département de Biologie IBENS - UMR ENS - CNRS 8197 - INSERM 1024 46 rue d'Ulm, 75230 Paris Cedex 05, FRANCE

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Barcelona Supercomputing Center: PhD student in Computer Science and Bioinformatics (R1)
by BSC RRHH 11 Jul '19

11 Jul '19

PhD student in Computer Science and Bioinformatics (R1) Reference: 194_19_LS_ICB_R1 *Context And Mission* Professor Nataša Pržulj is looking for several PhD students to work in machine learning and network science. They will be developing new algorithms for computationally hard problems and applying them to analyzing large-scale molecular and patient data to aid drug discovery and personalizing treatment. The successful candidates will work on the prestigious ERC Consolidator grant of Prof. Pržulj. The successful candidates will complete a PhD in Computer Science, which will address developing and applying sophisticated machine learning and network science models and algorithms. The algorithms will be carefully tuned to extract relevant biological and medical knowledge from systems-level real-world molecular and medical data. The aim is to utilize them to understand the structure of the data that would enable mining the data for new biological and medical insight that would further lead to improving diagnostics, discovering new biomarkers, improving patient stratification and treatment, personalizing treatment and facilitate rational drug development. The successful candidates will join a dynamic research group of Prof. Przulj within BSC. The students will work in a highly sophisticated HPC environment, will have access to systems and computational infrastructures, and will establish collaborations with experts in different areas. *Key Duties* * Complete a PhD in computational biology * Collaborate with various research groups across Europe and elsewhere MORE INFO & APPLY HERE: https://www.bsc.es/join-us/fellowships/19419lsicbr1 http://bsc.es/disclaimer

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