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Fwd: FW: Vacatures PhD NET Antwerpen
by Berry Kriesels 30 Jun '16

30 Jun '16

*Onderwerp:* Vacatures PhD NET Antwerpen Hallo collega’s, Dankzij een Kom op tegen Kanker-beurs, kunnen we de Antwerpse NET-groep verder uitbouwen. Hiervoor zijn we op zoek naar twee nieuwe PhD-studenten: een bio-informaticus en (bij voorkeur) een arts-onderzoeker. Beide onderzoekers zouden, vanuit Antwerpen, aan ons gemeenschappelijke onderzoeksproject werken (inclusief een nog op te starten NET-biomerker-trial). De arts-onderzoeker zou hierin ook wat mijn rol overnemen, aangezien ik vanaf augustus 2016 aan mijn klinisch opleiding begin. Aangezien beide profielen niet zo eenvoudig in te vullen zijn, wou ik vragen of jullie eventueel nog kandidaten wisten/de vacatures konden verspreiden? Meer info over de vacatures vinden jullie hier: · Clinical researcher, PhD project <https://www.uantwerpen.be/en/jobs/vacancies/ap/2016bapfggwef167/> · Bio-informatician/PhD student <https://www.uantwerpen.be/en/jobs/vacancies/ap/2016bapfggwef168/> Met vriendelijke groeten, Timon. *--- Timon Vandamme, MD PhD fellow - Medical Oncology resident* Human Molecular Genetics Prins Boudewijnlaan 43, 2^nd floor B2650 Edegem, Belgium Department of Oncology Antwerp University Hospital Wilrijkstraat 10 B2650 Edegem, Belgium e-mail | timon.vandamme(a)uantwerpen.be <mailto:timon.vandamme@uantwerpen.be> e-mail | timon.vandamme(a)uza.be <mailto:timon.vandamme@uza.be> /Please consider the environment before printing this message./

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STATS COURSE - Landscape (population) genetic data analysis using R'
by Oliver Hooker 29 Jun '16

29 Jun '16

"Landscape (population) genetic data analysis using R” Delivered by Dr. Rodney Dyer http://prstatistics.com/course/introduction-to-phylogenetic-analysis-with-r… This course will run from 17th – 21st October 2016 at SCENE Field Station, Loch Lomond, Glasgow, Scotland The term ‘landscape genetics’ has been applied studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration. This course will cover the basics of both quantitative landscape ecology and population genetics, focusing on how we develop and evaluate spatial/genetic analyses using the R platform Course content is as follows Day 1 • Spatial & Ecological Data • Installation & configuring R & RStudio • Acquiring spatial data, projections, and visualization • Vector and raster data Day 2 • Genetic markers and basic analyses • Genetic markers and sampling • Genetic distance, diversity, and structure • Ordination techniques based upon genetic markers Day 3 • Integrating spatial and genetic data • Barrier detection & population division • Resistance Modeling • Mantel and distance regressions • Remote sensing - LiDAR and Hyperspectral data Day 4 • Integrating spatial and genetic data • Spatial autocorrelation • Network Approaches • PCMN & Redundancy Day 5 • Adaptive Genetic Variance • Outliers & gradients • Quantitative genetics, why we should care. • Chromosome walking Please email any inquiries to oliverhooker(a)prstatistics.com or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhooker(a)prstatistics.com 1. ADVANCES IN SPATIAL ANALYSIS OF MULTIVARIATE ECOLOGICAL DATA (July) 2. INTRODUCTION TO BIOINFORMATICS USING LINUX (August) 3. GENETIC DATA ANALYSIS / EXPLORATION USING R (August) 4. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August) 5. INTRODUCTION TO PYTHON FOR BIOLOGISTS (October) 6. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October) 7. PHYLOGENETIC DATA ANALYSIS USING R (Octobe/November) 8. SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (November) 9. ADVANCING IN STATISTICAL MODELLING USING R (December) 10. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January) 11. ADVANCED PYTHON FOR BIOLOGISTS (February) 12. NETWORK ANALYSIS FOR ECOLOGISTS USING R (March) 13. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June) Dates still to be confirmed - email for details oliverhooker(a)prstatistics.com • STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R • INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS • BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS Oliver Hooker PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/ -- Oliver Hooker PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/

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PhD studentship in constructive machine learning for synthetic engineering of microbial organisms at Ghent University
by Willem Waegeman 29 Jun '16

29 Jun '16

Fully-funded PhD studentship in constructive machine learning for synthetic engineering of microbial organisms at Ghent University --- Duration of studentship: 4 years Studentship start date: flexible between October 2016 and February 2017 Application closing date: August 15th (will be extended if no suitable candidate is found). Apply as soon as possible to avoid disappointment! --- Project description: Turning organisms into highly-efficient microbial cell factories is a daunting process due to the enormous cellular complexity, i.e., the vast metabolic network superimposed by a multi-level regulatory layer and the fragmentary knowledge thereof. Typically, to steer the strain engineering process a “Design-Build-Test” (DBT) cycle is iteratively run. However, to move more successfully through this cycle and, hence, to more successfully engineer biological systems some major limitations need to be overcome: i) bottlenecks identified in silico by data-driven and/or model-based approaches are often not yielding the expected outcome in vivo (“Design”), and ii) the DNA parts and engineering tools, originating from synthetic biology, perform often inconsistently (“Build”), equally impeding reliable biological engineering. In the proposed project, we aim to solve these limitations by developing novel constructive machine learning and synthetic biology tools that jointly allow such reliable biological engineering. Constructive machine learning describes a class of related machine learning problems where the ultimate goal of learning is not to find a good model of the data but instead to find one or more particular instances of the domain which are likely to exhibit desired properties. While traditional approaches choose these domain instances from a given set/databases of unlabeled domain instances, constructive machine learning is typically iterative and searches an infinite or exponentially large instance space. Background information: The studentship is available as a joint initiative between the research unit KERMIT under supervision of Prof. Willem Waegeman and the research unit MEMO under supervision of Prof. Marjan De Mey. Both research units are part of the Faculty of Bio-science Engineering of Ghent University. KERMIT (acronym for Knowledge Extraction and Representation Management by means of Intelligent techniques) is a young interdisciplinary team of mathematicians, engineers and computer scientists, and it draws upon intelligent techniques resulting from the cross-fertilization between the fields of computational intelligence and operations research. The main focus is on mathematical and computational aspects of relational structures as knowledge instruments, with emphasis on the fields of fuzzy set theory and machine learning. KERMIT serves as an attraction pole for applications in the applied biological sciences, and serves colleagues in hydrology, ecology, bacterial taxonomy, genome analysis, integrated water management, geographical information systems, forest management, metabolic engineering, soil science, bioinformatics, systems biology, etc. MEMO (Metabolic engineering of microorganisms) focuses on the development of novel tools and methods to fine tune metabolic pathways for the biosynthesis of chemically complex metabolites. These novel tools and technologies include several DNA parts libraries as well as efficient and rapid methods for constructing synthetic pathways, transferring them into prokaryotic or eukaryotic microbial systems, and screening them in a high-throughput manner. We apply these tools and methods to create custom designed microbes for the production of useful chemicals from renewable resources, in particular for the production of specialty carbohydrates and natural products. These molecules, or their direct precursors, have a myriad of high-added value applications in - among others- pharmaceuticals, food additives and cosmetics. The ideal candidate for the position has the following profile: •An MSc degree in (Bio-)Engineering, Bio-informatics, Computer Science, Mathematics, Statistics, Physics, or equivalent – candidates from outside Belgium are welcome to apply. •An interest for fundamental machine learning research, as well as practical applications in synthetic biology. •In-depth experience with at least one programming language (Matlab, R, Python, Java, etc.) •An interest for applied mathematics, data management and data analysis in general •Good knowledge of machine learning and statistical methods is a strong asset •Good knowledge of molecular and synthetic biology is a strong asset •Fluent in English (speaking and writing, as demonstrated by personal texts) •Knowledge of Dutch is an asset, but not a must •Team player with good communication skills How to apply Send your c.v., a motivation letter, a copy of your MSc.-thesis and/or any relevant publications to Ruth Van Den Driessche (ruth DOT vandendriessche AT ugent DOT be).

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Still time to apply: Post-doctoral positions in Luxembourg
by Francisco Azuaje 29 Jun '16

29 Jun '16

Dear colleagues, We are seeking post-doctoral researchers to contribute to an international cooperation project in network analysis approaches and their application to cancer research. https://www.lih.lu/jobs/detail/2-post-doctoral-researchers-fa0416-12452 Sincerely, Francisco. _________________________________ Francisco Azuaje, PhD Principal Investigator NORLUX Neuro-Oncology Laboratory Department of Oncology Luxembourg Institute of Health 1A-B, rue Thomas Edison, L-1445 Strassen Luxembourg Tel: +352 26970-875 Fax: +352 26970-719 Email: francisco.azuaje(a)lih.lu<mailto:francisco.azuaje@lih.lu> Website: https://www.lih.lu/ [http://files.lih.lu/outlookSignature/lih.jpg] Join us on Facebook and follow our activities on Twitter: https://www.facebook.com/Luxembourg.Institute.of.Health http://twitter.com/LIH_Luxembourg http://www.norlux.lu This message (including any attachments) is intended for the addressee only and may contain confidential and/or privileged information and/or information protected by intellectual property rights. If you have received this message by mistake, please notify the sender by return e-mail and delete this message from your system. You should not use, alter, copy or distribute this message or disclose its contents to anyone. E-mail transmission can not be guaranteed to be secure or error free as information could be intercepted, corrupted, lost, destroyed, arrive late or incomplete, or contain viruses. Luxembourg Institute of Health shall not be responsible nor liable for the proper and complete transmission of the information contained in this communication nor for any delay in its receipt or damage to your system.

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looking for a PhD-candidate at Maastricht Centre for Systems Biology
by Lenz Michael (MACSBIO) 28 Jun '16

28 Jun '16

Dear Colleague We are currently looking for a PhD-candidate to integrate multi-dimensional data from human studies with computational and mathematical metabolic models in the field of type 2 diabetes and cardiovascular disease. I wonder if you would be kind enough to circulate this information to potential candidates in your Institute. Yours sincerely, Ilja Arts PhD position MaCSBio (Maastricht Centre for Systems biology) The Maastricht Centre for Systems Biology (MaCSBio) aims to integrate biological data from different empirical domains using multi-scale modelling approaches. One of MaCSBio's research lines focusses on Systems Medicine of Chronic Diseases, with the aim of developing more personalized preventive strategies for obesity-related chronic diseases, such as type 2 diabetes, cardiovascular disease, or cancer. In this research line, our main interest is in the integration of large, multi-dimensional data from various human studies with computational and mathematical metabolic models. We are currently looking for a PhD candidate that helps us to strengthen our research activities in the field of metabolic modelling. The main focus of the PhD project will be on the analysis of cell-type specific metabolic aberrations related to preclinical stages of type 2 diabetes and cardiovascular disease. This will be achieved by the integration of various omics datasets (transcriptomics, proteomics, metabolomics) from cohort and intervention studies with state-of-the-art human genome-scale metabolic models, such as Recon 2. Integration of these different data types with the available knowledge from the network reconstructions will be done based on topological network analysis, as well as constraint-based analysis methods with flux balance analysis and random sampling approaches. The research will be performed in close collaboration with other researchers at MaCSBio, the university and academic hospital, and our international partners. This will enable the integration of the described research into a broader modelling approach towards a systems-wide understanding of chronic diseases. We are looking for: A candidate who has the ambition to become a specialist in metabolic modelling related to chronic diseases and who has the ambition and the competences to think and work outside the usual disciplinary boxes. Furthermore, the PhD candidate: *holds a MSc degree in computational or mathematical biology, systems biology or other related fields of study *has strong interest in and a working knowledge of human biology and especially human metabolism *works in a highly independent and self-motivated manner *has programming experience related to computational modelling (e.g. MATLAB), data modelling (e.g. R), or analytical applied programming languages (e.g. Python). *has a basic understanding of mathematical modelling and statistics *has good communication skills and speaks English fluently You can find more information and apply for the job via https://www.academictransfer.com/employer/UM/vacancy/34665/lang/en/ [Lustrumlogo 2016] [LogoMaCSBio] Prof. Dr. Ir. Ilja C.W. Arts, PhD Professor of Molecular Epidemiology of Chronic Diseases Scientific Director Maastricht Centre for Systems Biology (MaCSBio) www.maastrichtuniversity.nl<http://www.maastrichtuniversity.nl/> macsbio.maastrichtuniversity.nl<http://macsbio.maastrichtuniversity.nl/> www.M2E2.nl<http://www.m2e2.nl/> ilja.arts(a)maastrichtuniversity.nl <mailto:ilja.arts@maastrichtuniversity.nl> Peter Debyeplein 1, 6229 HA, Maastricht P.O. Box 616, 6200 MD Maastricht, The Netherlands T +31 43 3882971 F +31 43 3884128 M + 31 6 15623990

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Abstract submission deadline for ESCS 2016 extended to 12 July
by ISCBSC announcement 27 Jun '16

27 Jun '16

Dear colleague, The abstract submission deadline for ESCS 2016 has been extended to Tuesday 12 July. The ESCS is a biennial interdisciplinary symposium that brings together students and young researchers from computational biology, bioinformatics, systems biology, and related fields. This symposium offers you a great opportunity to present your research to an international audience, get insights into hot topics and newly developed methods and build a network within the computational biology community of Europe. We are pleased to announce our three confirmed keynote speakers Kris Laukens (University of Antwerp, Belgium), Yves Van de Peer (Ghent University, Belgium), and Nuria Lopez-Bigas (Universitat Pompeu Fabra, Spain). The symposium includes ice-breaking, oral presentations, keynote talks, poster presentations and an evening social event that offer you the opportunity to get to know fellow young scientists from all over Europe in a casual setting. Tuesday 12 July 2016: Abstract submission deadline for oral presentations closes. Please visit http://submit.iscbsc.org/escs to submit your abstract and read the abstract guidelines here <http://escs2016.iscbsc.org/escs2016-abstract-guidelines>. Friday 22 July 2016: Abstract submission deadline for poster presentations closes. Please visit http://submit.iscbsc.org/escs to submit your abstract and read the abstract guidelines here <http://escs2016.iscbsc.org/escs2016-abstract-guidelines> and the poster guidelines here <http://escs2016.iscbsc.org/escs2016-poster-guidelines>. Friday 22 July 2016: Travel fellowship application deadline closes. Please visit submit.iscbsc.org/escs to submit your travel fellowship application and read the travel fellowship guidelines here <http://escs2016.iscbsc.org/2016-TF-Call-Guidelines>. Friday 29 July 2016: The early bird registration deadline for ESCS 2016 closes. please visit http://www.eccb2016.org/registration/ to register for ESCS 2016. We welcome students and young researchers from all areas of computational biology to join our community. Please help us spread the word by sharing the event flyer (please find it attached), and using the hashtag #ESCS16 on social media. Please visit our website http://escs2016.iscbsc.org/ regularly as more information will be announced soon. We look forward to welcome you in The Hague! Annika Jacobsen and Kevin Schwahn, chair and co-chair, ESCS 2016

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Phylogenetic data analysis using R
by Oliver Hooker 23 Jun '16

23 Jun '16

"Introduction to phylogenetic analysis with R" Delivered by Dr. Emmanuel Paradis http://prstatistics.com/course/introduction-to-phylogenetic-analysis-with-r… This course will run from 31st October – 4th November, Millport Field Station, Ilse of Cumbrae, Scotland The main objectives of the course are to teach the theoretical bases of phylogenetic analysis, and to give the ability to initiate a phylogenetic analysis starting from the files of molecular sequences until the interpretation of the results and the graphics. The introduction will cover a brief historical background and an overview of the different methods of phylogenetic inference. Different kinds of data will be considered, but with a special emphasis on DNA sequences. The software used will be based on R and several specialized packages (particularly ape and phangorn). Other software will be used (e.g., MUSCLE or Clustal) called from R. Overall, the course will cover almost all aspects of phylogenetic inference from reading/downloading the data to plotting the results. This course is intended for PhD and postgraduate students, researchers and engineers in evolutionary biology, systematics, population genetics, ecology, conservation. Course content is as follows Day 1 • Refresher on R: data structures, data manipulation with the indexing system, scripts, using the help system. • Introduction to phylogenetic inference. • Basics on phylogenetic data (sequences, alignments, trees, networks, “splits”) and other data in R. • Reading / writing data from files or from internet. • Matching data. Manipulating labels. Subsetting data. • Main package: ape. Day 2 • Plotting and annotating trees. • Theory of sequence alignment. Comparing alignments. Graphical analyses of alignments. • Main packages: ape (with MUSCLE and Clustal). Day 3 • Theory and methods of phylogeny reconstruction. • Parsimony methods. • Evolutionary distances. • Distance-based methods: General principles and the main methods (NJ, BIONJ, FastME, MVR). • Methods for incomplete distances matrices (NJ*, BIONJ*, MVR*). Methods for combining several matrices (SDM). • Main packages: ape, phangorn. Day 4 • Theory of maximum likelihood estimation. • Application to phylogeny reconstruction. • Substitution models. • Tree space and topology estimation. • Main packages: ape, phangorn. Day 5 • Tree comparison, consensus methods. • Topological space and distances. • Bootstrap. • Bayesian methods. Please email any inquiries to oliverhooker(a)prstatistics.com or visit our website www.prstatistics.com Please feel free to distribute this material anywhere you feel is suitable Upcoming courses - email for details oliverhooker(a)prstatistics.com 1. ADVANCES IN SPATIAL ANALYSIS OF MULTIVARIATE ECOLOGICAL DATA (July) 2. INTRODUCTION TO BIOINFORMATICS USING LINUX (August) 3. GENETIC DATA ANALYSIS / EXPLORATION USING R (August) 4. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (August) 5. INTRODUCTION TO PYTHON FOR BIOLOGISTS (October) 6. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (October) 7. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (October) 8. SPATIAL ANALYSIS OF ECOLOGIC AL DATA USING R (November) 9. ADVANCING IN STATISTICAL MODELLING USING R (December) 10. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January) 11. ADVACNED PYTHON FOR BIOLOGISTS (February) 12. NETWORK ANALYSIS FOR ECOLOGISTS (March) 13. INTRODUCTION TO GEOMETRIC MORPHOMETRICS USING R (June) Dates still to be confirmed - email for details oliverhooker(a)prstatistics.com • STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R • INTRODUCTION TO R AND STATISTICS FOR BIOLOGISTS • BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS Oliver Hooker PR statistics 3/1 128 Brunswick Street Glasgow G1 1TF +44 (0) 7966500340 www.prstatistics.com www.prstatistics.com/organiser/oliver-hooker/

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FW: Postdoc positions in Genomics and Computational Biology, Cambridge
by Sadaf Farooqi 22 Jun '16

22 Jun '16

Dear Colleague I wonder if you would be kind enough to circulate information about 2 postdoc positions we have recently advertised to scientists in your Institute. The area is genomics and computational biology in human disease; posts will be based at the Institute of Metabolic Science, University of Cambridge. More detailed information can be found in the attached adverts. Many thanks Sadaf Farooqi Professor Sadaf Farooqi PhD, FRCP, FMedSci Wellcome Trust Senior Clinical Fellow and Professor of Metabolism and Medicine University of Cambridge Metabolic Research Laboratories Level 4, Wellcome Trust-MRC Institute of Metabolic Science Box 289, Addenbrooke's Hospital Cambridge CB2 0QQ United Kingdom Tel: +44-1223-762634 Fax: +44-1223-762657 Email: isf20(a)cam.ac.uk GOOS website: www.goos.org.uk ________________________________________

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ELIXIR Belgium
by Kim DE RUYCK 21 Jun '16

21 Jun '16

Dear, I would like to introduce myself as the newly appointed coordinator for ELIXIR Belgium. I will coordinate the setup of the Belgian ELIXIR node and will be the central contact person. Initially, the main goal of ELIXIR Belgium is to establish communication and more collaboration between the different bioinformatics groups and work towards an active and integrated bioinformatics community. The working areas of ELIXIR Belgium include data resources, tools infrastructure, computational and training services. As such, ELIXIR Belgium is valuable to all bioinformaticians, life scientists and industries generating and analyzing data! The ELIXIR Belgium website will be launched soon, meanwhile you can find relevant information concerning tools, trainings, events, etc. on ELIXIR Europe . Our activities can be followed on Twitter ( @ ELIXIRnodeBE ). Feel free to follow us! Best regards, Kim Kim De Ruyck PhD Coordinator ELIXIR Belgium VIB, Technologiepark 927, 9052 GENT | +32 9 331 36 94 @ELIXIRnodeBE | bioinformatics.psb.ugent.be

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postdoctoral position in bioinformatics in University of Groningen
by Horvatovich, P.L. 20 Jun '16

20 Jun '16

Postdoc research position LC-MS/MS data preprocessing and statistical analysis (216165) Organisation The Faculty of Mathematics and Natural Sciences harbours a kaleidoscope of disciplines and research strengths. Our programmes in research and education range from nanomaterials and biomachinery to astronomy, from mathematics to pharmacy, from neurosciences to computer science, and from molecular and evolutionary biology to marine biology. Our researchers pursue fundamental key questions while collaborating with partners from industry, the medical world and other realms of society. Frontline research groups explore new fields such as synthetic biologyand sustainable energy use. Job description Development of single-stage LC-MS/MS data preprocessing and statistical analysis approaches for risk assessment of mycotoxin exposure through dietary intake in Qatar. This postdoctoral position is embedded within the interdisciplinary research groups of Analytical Biochemistry/Department of Pharmacy1 at the Faculty of Mathematics and Natural Science of the University of Groningen (RUG). Mycotoxins are the most ubiquitous carcinogenic contaminant in the human food supply leading to adverse consequences on human population such as hepatocellular carcinoma. Mycotoxin concentrations are regularly measured in food but their impact on human population health remain unclear. The aim of this project is to perform risk assessment of mycotoxin exposure of Qatar population through dietary intake in collaboration with scientists of the Anti Doping Lab Qatar2. In the research project the postdoctoral scientist is expected i) to develop and implement novel single stage, data dependent and data independent LC-MS(/MS) data pre-processing workflows based on Threshold Avoiding Proteomics3 pipeline and other open source tool such as OpenMS4, XCMS5 and mzMine6, and ii) statistical analysis of obtained molecular profile for mycotoxin exposure in pilot animal study and in human population and iii) perform risk assessment of human population in Qatar based on obtained data. The successful candidate will strongly benefit from working in a highly interdisciplinary research team composed of clinical researchers, analytical chemists, bioinformaticians and statisticians. The Analytical Biochemistry group has an excellent scientific infrastructure and track record in proteomics, proteogenomics and computational Mass Spectrometry1. Qualifications The candidate should have a strong background in mathematics and statistics and should have strong experience in C++, Matlab and/or R programming. Experience with data analysis in mass spectrometry would be a significant advantage. The candidate should be able to work in an interdisciplinary and multinational research team and have good communication skills. Conditions of employment The University of Groningen offers a salary that is determined in accordance with the rules as set out in the collective labour agreement for the Dutch Universities (CAO) and has a range between € 3,044 and € 3,997 (scale 10 Dutch Universities) gross per month depending on qualifications and experience based on a fulltime position. The position is temporary for one year. After a positive successful evaluation in the first year, the contract will be extended by 1.5 year. The University of Groningen offers an excellent research infrastructure and training programme to develop research skills of the successful candidate. Link references: 1 http://www.biomac.nl 2 http://adlqatar.net/ 3 Suits F, Hoekman B, Rosenling T, Bischoff R, Horvatovich P., Threshold-avoiding proteomics pipeline, Anal Chem. 2011, 15;83(20):7786-94. 4 Bertsch A, Gröpl C, Reinert K, Kohlbacher O., OpenMS and TOPP: open source software for LC-MS data analysis, Methods Mol Biol. 2011;696:353-67. 5 Mahieu NG, Genenbacher JL, Patti GJ., A roadmap for the XCMS family of software solutions in metabolomics, Curr Opin Chem Biol., 2016, 30:87-93. 6 Pluskal T, Castillo S, Villar-Briones A, Oresic M., MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data, BMC Bioinformatics. 2010, 11:395. Additional information and sending in of applications Applications with curriculum vitae and the names of three former or present supervisors who can be contacted as references should be sent until 14 July / before 15 July 2016 Dutch local time by means of the application form (click on the link below). Unsolicited marketing is not appreciated. Information For information you can contact: · Prof. P.L. Horvatovich, +31 50 3633341, p.l.horvatovich(a)rug.nl (please do not use for applications) *Apply <http://www.rug.nl/about-us/work-with-us/job-opportunities/overview?reply=00…>* or direct link: http://www.rug.nl/about-us/work-with-us/job-opportunities/overview?reply=00… -- Peter Horvatovich Associate Professor University of Groningen Faculty of Mathematics and Natural Sciences Department of Pharmacy Analytical Biochemistry Building 3226, Room 6.9 Antonius Deusinglaan 1 9713 AV Groningen Internal Zip Code XB20 P.O. Box 196 9700 AD Groningen The Netherlands Telephone: +31-(0)50-363 3341 Fax: +31 (0)50 363 7582 Mobile: +31 (0)6 2459 7203 Email: p.l.horvatovich(a)rug.nl Homepage: www.biomac.nl

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