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    Latest announcements

    BACKGROUND

    Applications are invited for an experienced and highly motivated individual to lead the training of biomedical scientists in data science and computational biology skills. The successful candidate will play a key role in a new strategic programme in Computational Biology and Biomedical Data Science Training within the Centre for Computational Biology in the MRC Weatherall Institute for Molecular Medicine. The programme's mission is to provide substantial expertise and to add value to ongoing research across the University of Oxford by training and mentoring biomedical scientists in data science and computational biology skills, methods and working practices.

    RESPONSIBILITIES

    The Computational Biology Trainer will be involved in the day-to-day management of the programme, including planning and delivering bioinformatics training, supervising fellows in computational biology research projects, and leading collaborative research projects in computational genomics.

    REQUIREMENTS

    You will hold a PhD in a quantitative discipline e.g. computational biology, bioinformatics, physics, statistics or related discipline. Previous experience in organising and delivering data science/computational biology training is essential. You will have experience of working in a Linux operating system and proficient in a least one programming language (e.g. Python, R). Excellent interpersonal and communication skills, with the ability to convey concepts to other scientists in different fields of research are essential. Experience in computational genomics is highly desirable.

    TERMS

    The position is available full-time and fixed-term until 31 March 2021, funded by the Oxford Biomedical Research Centre. Applications from those wishing to work part-time as a 50% job share are welcome (please state this clearly in your application).

    LOCALE

    Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, MRC WIMM Centre for Computational Biology, John Radcliffe Hospital, Headington, Oxford

    COMPENSATION

    Grade 8: £39,922 - £47,722 p.a.

    HOW TO APPLY

    Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application. www.recruit.ox.ac.uk/pls/[...]32940

    DEADLINE

    The closing date for this position is 12.00 noon on Monday 19 February 2018. Interviews will be held in early March 2018.

    BACKGROUND

    The Ressom Lab (omics.georgetown.edu) at Georgetown Lombardi Comprehensive Cancer Center has an immediate opening for a post-doctoral research associate in bioinformatics to work in a multi-disciplinary environment on cancer biomarker discovery and systems biology research.

    RESPONSIBILITIES

    The candidate will be responsible for analysis of omic data acquired by high-throughput technologies such as mass-spectrometry and next generation sequencing. This includes: (1) pre-processing of mass-spectrometric and next generation sequencing data; (2) identification of differentially altered molecules by statistical and network-based methods; and (3) integration of multi-omic data by network-based and machine learning methods to identify cancer biomarkers and to advance systems biology research.

    REQUIREMENTS

    The position requires a Ph.D. degree in bioinformatics, computer science, engineering, biostatistics, or related field with relevant experience in computational biology. In addition, applicants should have demonstrated research experience in omic data analysis and machine learning methods such as deep learning.

    PREFERENCES

    Programming skills in R, MATLAB, or Python are highly desirable.

    COMPENSATION

    $48,000 - $55,000 per year

    HOW TO APPLY

    Applicants are requested to email their CV and names of three references to Prof. Ressom at hwr[at]georgetown.edu
    Education: Book and online course: Biostar Handbook
    Submitted by Steven Allford; posted on Wednesday, January 17, 2018

    Submitter

    UPDATES TO THE BIOSTAR HANDBOOK

    The answers to some of the greatest questions of life lie within ourselves. Bioinformatics is the new science created by fusing Biology and Data Science.

    Since its release at the end of 2016, the Biostar Handbook has been continuously expanded, improved, and enriched to become one of the most comprehensive and systematic presentations of Bioinformatics from a Data Science perspective: biostar.myshopify.com

    Since its release, the book has been adopted across the globe in several universities and research centers. In addition, over the course of the last year, the Biostar Handbook has been expanded with several new chapters covering Metagenomics and ChIP-Seq analysis.

    With the help of the e-book, readers are able to reproduce analytics results from realistic, and cutting-edge data analysis scenarios such as genome variation, SNP calling, genome assembly and RNA-Seq based gene expression studies: www.biostarhandbook.com

    In the Fall of 2017 an online Bioinformatics Course titled "Learn Bioinformatics in 100 hours" has been added to the book and made available to the readers free of charge: www.biostarhandbook.com/edu/course/1/

    The online course provides a structured path through the book and includes assignments and thorough tests and evaluations.

    The Biostar Handbook is the most affordable, low-cost option to get introduced to this new scientific domain. Join the thousands of readers, hundreds of enrolled students that are currently progressing through the book. With the help of the Biostar Handbook, you too can connect to the new generation of scientists that are well prepared to handle the challenges of the data-centric life sciences.

    BACKGROUND

    Cancer is a major cause of death and suffering. It constitutes a group of diseases characterized by abnormal cell growth, stage-wise progression, heterogeneity, and potential to develop resistance to therapies. All these aspects are consequences of the evolutionary nature of cancer. Fortunately, genomics has recently begun to provide opportunities for unprecedentedly detailed insights into tumour evolution. New techniques are presently emerging for assaying the spatial distribution of tumour heterogeneity, and future yet unforeseen experimental breakthroughs are inevitable.

    CONTRA (itn-contra.org) is a H2020 Marie-Sklodowska-Curie Innovative Training Network aimed at providing a structured training programme to 15 Early Stage Researchers (ESRs) to study tumor evolution using computational techniques upon novel experimental data including, but not limited to, single-cell genomic data. See the list of projects at the end of this message.

    The training structure of CONTRA will include local and network-wide activities and secondments to other labs in the network. Most positions are for 3 years and some for 4 years, contracts starting approximately July 1, 2018, but all of them lead to a PhD degree.

    For individual descriptions of the 15 projects, please use the following link: itn-contra.org/esr-projects/.

    List of projects, including supervisor and host institution:
    ESR1: Comparing tumour phylogenies from single cell data versus bulk sequencing data. Florian Markowetz, University of Cambridge, Cambridge, UK.
    ESR2: The mechanisms of coding and non-coding oncogenic alterations. Nuria Lopez-Bigas, IRB, Barcelona, Spain.
    ESR3: Identification of drivers of relapse and metastasis. Nuria Lopez-Bigas, IRB, Barcelona, Spain.
    ESR4: Estimating tumour phylogenies from single-cell SNV and CNA data. Niko Beerenwinkel, ETH Zurich, Basel, Switzerland.
    ESR5: Evolutionary history of circulating tumour cells and distant metastases. Ewa Szczurek, University of Warsaw, Warsaw, Poland.
    ESR6: Identification and impact of clonal and subclonal driver alterations on cancer progression. Francesca Ciccarelli, KCL/Crick Institute, London, UK.
    ESR7: Inferring tumour evolution and migration. Niko Beerenwinkel, ETH Zurich, Basel, Switzerland.
    ESR8: Models and inference for Single-cell sequencing and tumour evolution. Jens Lagergren, KTH, Stockholm, Sweden.
    ESR9: Evolution of drug resistance on genetic and phenotypic levels. Ewa Szczurek, University of Warsaw, Warsaw, Poland.
    ESR10: Driver events, evolutionary dynamics and interplay with the external environment across cancer types. Francesca Ciccarelli, KCL/Crick Institute, London, UK.
    ESR11: Estimation of tumour growth rates from NGS data. David Posada, University of Vigo, Vigo, Spain.
    ESR12: Mutational patterns and models within tumours. David Posada, University of Vigo, Vigo, Spain.
    ESR13: Integrated image and genomics. Yinyin Yuan, ICR, London, UK.
    ESR14: Spatial genetics and transcriptomics of pancreatic and ovarian cancer. Florian Markowetz, University of Cambridge, Cambridge, UK.
    ESR15: Reconciling tumour trees and multiple tumour progression models. Jens Lagergren, KTH, Stockholm, Sweden.

    COMPENSATION

    H2020 EU funding imposes strict eligibility criteria. At the time of recruitment the researcher must not have resided or carried out his/her main activity (work, studies, etc...) in the country of the host institute for more than 12 months in the three years immediately prior to his/her recruitment. The researcher should also be in the first four years of their research careers at the time of recruitment by the host organisation and have not been awarded a doctoral degree. The successful candidate will receive a very generous financial package. The exact conditions varies across the universities, but the gross amounts of EU funding for an ESR is in the range 3710€-4210€. The net salary will result from deducting all compulsory (employer/employee) social security contributions as well as direct taxes from the gross amounts, according to the law applicable to the agreement concluded with the ESR. Some universities will also supplement the EU funding. For details see the EU Guide for applicants (goo.gl/d6LtsE).

    HOW TO APPLY

    Candidates may apply for the positions through the KTH application system (goo.gl/yTThgg). The application should include the following documents:
    1. Curriculum vitae with at most 3 pages
    2. Transcripts from University / University College
    3. Contact details for three references
    4. Brief description of why the applicant wishes to become a PhD student within this network
    5. Ranking of 3 ESR projects based on the applicant's preference

    Each project supervisor will revise the candidates' documentation and, on the basis of the completeness and adequacy of the requested material and eligibility, will score candidates based on: (1) academic profile; (2) personal motivation; (3) scientific skills and relevant experience; and (4) English proficiency. Shortlisted candidates will be invited to teleconference interviews with the relevant project supervisor(s).

    Candidates are invited to contact the supervisors for more details.

    DEADLINE

    Application deadline: 23:59 CET on 15 February 2018.

    POLICY

    Specific conditions may apply to individual positions depending on local regulations. Top-level graduates (master degree or equivalent) in bioinformatics, statistics, mathematics, computer science or evolutionary biology are encouraged to apply. No discrimination will be made on the basis of nationality, gender, race, religion or disability.

    BACKGROUND

    The Center for Systems Biology Dresden (CSBD) calls for applications for ELBE postdoctoral fellowships in the fields of

    Bioinformatics and Computational Biology

    The ELBE postdoctoral fellows program fosters cross-disciplinary projects and provides an ideal springboard to an independent research career.

    REQUIREMENTS

    What we seek:
    We seek outstanding young researchers with a doctoral degree in computer science, (applied) mathematics, or bioinformatics and a strong commitment to work in a multi-disciplinary environment on Biological Sequence Analysis, Bioimage Informatics, Computer Simulation of biological systems, Comparative and Evolutionary Genomics, High-Performance Computing, or Network Biology. ELBE postdoctoral fellows are expected to collaborate with more than one research group to bridge between disciplines.

    COMPENSATION

    What we provide:
    The CSBD provides 1-3 year fully funded positions in an international and cross-disciplinary research environment. ELBE postdoctoral fellows benefit from close collaborations with scientists at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), the Max Planck Institute for the Physics of Complex Systems (MPI-PKS), and the Technische Universität Dresden (TU Dresden). They have full access to state-of-the-art research facilities and infrastructure on the campus. ELBE postdoctoral fellows have the freedom to develop their own research questions.

    HOW TO APPLY

    For details about the application procedure, please visit our website: www.csbdresden.de/join[...]tdoc/. Selection of ELBE Fellows is highly competitive with two application cycles per year. Short-listed candidates are invited to on-site interviews with travel costs covered by the CSBD.

    DEADLINE

    Deadline for applications is March 4, 2018.

    POLICY

    The Max Planck Society is an equal opportunity employer: handicapped individuals are strongly encouraged to apply. The Center for Systems Biology, the MPI-CBG and the MPI-PKS aim to increase the number of women in scientific positions. Female candidates are therefore particularly welcome.

     

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