BOL: Related items

Ph.D. student in Computational Systems Biology

Tue, 10 Dec 2013 18:46:05 -0600

Ph.D. student in Computational Systems Biology

Location : The Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, Luxembourg, Luxembourg
Deadline for applications : unknown.
Description :

The Luxembourg Centre for Systems Biomedicine (LCSB) was created within the Health Technologies Initiative from the Government of Luxembourg as one of the research priorities of the University of Luxembourg. The LCSB is an Interdisciplinary Centre of the University that combines experimental and computational approaches to analyse complex biological systems and disease processes. The Computational Biology Group (CBG) provides the LCSB with a solid infrastructure in developing theoretical framework for computational modeling on biomedical problems, especially in the area of network biology in the context of cellular programming/reprogramming. The CBG group includes researchers with theoretical, computational and wet lab backgrounds, thereby providing an unusually interdisciplinary environment.
The Computational Biology Group seeks a highly-skilled Ph.D. student to work on an exciting project on reconstruction and analysis of an integrated gene regulatory network model to elucidate key mechanisms of cellular reprogramming. The model will rely on the integration and mining of diverse transcriptomics and epigenomics data of different cell types from the Central Nervous System. The Ph.D. student is expected to collaborate with other members of the CBG to develop a computational methodology aiming at designing, in-silico, cellular reprogramming events, with a focus on the nervous system. This project will be carried out in collaboration with Prof. Noel Buckleys lab at Kings College London.
Requirements of the ideal candidate:
Master degree in Bioinformatics, Computer Science, Biology or a related discipline
Prior experience in mathematical modelling of biological networks, especially in network inference and analysis
Excellent working knowledge in English.
.
We offer:
Full contract for Ph.D. student for three years with possibility of renewal
Opportunity to do applied research to medical problems within a highly dynamic research institution (LCSB) and in collaboration with internationally recognized partners
An exciting international environment
A very competitive salary

For further information, please contact:

Prof. Dr. Antonio del Sol
E-mail: antonio.delsol@uni.lu

Applications should contain the following documents:
A detailed curriculum vitae
cover letter mentioning the reference number
description of past research experience and future interests
name and addresses of three referees

All applications should be sent preferably in electronic version until December 31st, 2013 to the following address:

Luxembourg Centre for Systems Biomedicine (LCSB)
University of Luxembourg
7, avenue des Hauts-Fourneaux
L-4362 Esch-sur-Alzette
Tel: +352-466644-6982 (Office)
Email: antonio.delsol@uni.lu
http://www.lcsb.lu

Scientist-B (Bioinformatics) at AIIMS, Delhi

Sun, 20 Dec 2020 04:34:55 -0600

Name of the Project: “Artificial intelligence in Oncology, Harnessing big data and advanced computing to provide personalized diagnosis and treatment for Cancer patients”

Age Limit: 35

How to Apply for the AIIMS Life Science Job:

Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.
Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.
No TA/DA will certainly be paid for appearing in the interview.
Note, The institute reserved the right to fill up or not to fill up the post advertised.

Emoluments: Rs. 56,000/- plus 24 percent HRA

Eligibility:
2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University
1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.
Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.

Desirable Qualifications:
Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.
Experience of Deep learning applications in biological data ( image/text).
Proficient in Rf Python machine learning libraries.
Prior experience in the cancer-related project (ML-based) will be advantageous.
Experience with PyTorch/TensorFlow will certainly be very desirable.
Applicant should have strong scientific writing as well as. verbal abilities.
Papers in sci-indexed journals demonstrating ML skill sets.
Database handling will certainly be plus yet not required.

More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf

Research Fellow @ Mendel laboratory

Tue, 26 Nov 2013 00:07:57 -0600

IRCCS Casa Sollievo della Sofferenza – Mendel laboratory is seeking one talented bioinformatician (Rome)
Start date: immediate

Duration: 1 year

Funding Source: Institutional
Salary on grant: B2 (€ 22.000/year gross)
Contact Person (Referent): Tommaso Mazza
Ref. E-Mail: t.mazza@css-mendel.it
Tel: +39 06 44160526
Fax: +39 06 44160548

Job Description: The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young PhD bioinformatician with specific experience and/or interest in the analysis of transcriptomic data.

The candidate will be mainly in charge of developing research on a range of hot applications and projects, dealing with microarrays, RNA-Seq and miRNA-Seq data. Main activities will be: (i) data analysis (short-reads mapping, variants call and annotation, functional enrichment analysis of gene expression data); (ii) networks analysis and simulation (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iii) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.

The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working with high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.
Knowledge of molecular modeling and simulation and one of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.

A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza, CSS-Mendel: t.mazza@css-mendel.it

Context
Casa Sollievo della Sofferenza is an Institute for hospitalization, care, and scientific research located in San Giovanni Rotondo, Italy. It integrates clinical assistance (with inpatient and outpatient facilities) and research. It has an affiliate institute, CSS-Mendel, located in Rome. Between the two sites, it employs over 100 researchers who focus on genetics. The Center is equipped with state of the art genomics technology (SOLiD 5500XL next generation sequencer, Illumina MiSeq, Affymetrix/Agilent microarray platforms, etc) as well as a dedicated high performance computing facility, a non-conventional workstation of GPUs and a short- and long-term storage disk.

Applications
Candidates should send:
• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;
• a CV including a list of publications;
• List of referees;

More at http://www.css-mendel.it/

Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)

Sun, 16 Feb 2020 02:57:40 -0600

https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
Your profile:
Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing
Strong competence in working in Unix/Linux environments (shell)
Strong programming skills (in particular: Python, R, Perl)
Experience with using git and snakemake
Fluent English language skills, both spoken and written
Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

Bioinformatics group at Boku University

Thu, 12 Dec 2013 17:53:10 -0600

The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine

1. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and
2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)

Lab page @ http://bioinf.boku.ac.at/

Choosing the Right NGS Sequencing Instrument for Your Study

Neel — Wed, 15 Jun 2022 00:37:29 -0500

The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you’re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our free consultation form and we'll get in touch with you to help.

More at https://genohub.com/ngs-instrument-guide/

Address of the bookmark: https://genohub.com/ngs-instrument-guide/

Free math books

Manisha Mishra — Thu, 12 Dec 2013 19:38:34 -0600

Bioinformatics require some match skills, therefore I decided to provide this wonderful math eBooks links to the BOL community.

Please add ur links/bookmarks in comment section.

Address of the bookmark: http://physicsdatabase.com/free-math-books/

Common steps for reads mapping !

BioStar — Thu, 09 Mar 2023 02:48:02 -0600

Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:

Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.
Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.
Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.
Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.
Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.
Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.

Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.

Bioinformatics software for biologists in the genomics era

Poonam Mahapatra — Sun, 22 Dec 2013 17:31:05 -0600

The genome sequencing revolution is approaching a landmark figure of 1000 completely sequenced genomes. Coupled with fast-declining, per-base sequencing costs, this influx of DNA sequence data has encouraged laboratory scientists to engage large datasets in comparative sequence analyses for making evolutionary, functional and translational inferences. However, the majority of the scientists at the forefront of experimental research are not bioinformaticians, so a gap exists between the user-friendly software needed and the scripting/programming infrastructure often employed for the analysis of large numbers of genes, long genomic segments and groups of sequences. We see an urgent need for the expansion of the fundamental paradigms under which biologist-friendly software tools are designed and developed to fulfill the needs of biologists to analyze large datasets by using sophisticated computational methods. We argue that the design principles need to be sensitive to the reality that comparatively small teams of biologists have historically developed some of the most popular biological software packages in molecular evolutionary analysis. Furthermore, biological intuitiveness and investigator empowerment need to take precedence over the current supposition that biologists should re-tool and become programmers when analyzing genome scale datasets.

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/23/14/1713.full

1mb long DNA with Nanopore technology

Jit — Tue, 19 Dec 2017 18:49:28 -0600

The first continuous DNA read of more than a million bases (>1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO