1) Senior Research Fellow under ICMR Project: M.Sc. (Life Sciences) with 2 years of experience (preferable in the field of Bioinformatics) or MBBS Degree.

2) Research Associate under ICMR Project: . Ph.D.(Life Science/Biotechnology/Bioinformatics) or equivalent degree or having 3 years of research, teaching and design and development experience after M.Tech with at least one research paper in science Citation Indexed (SCI) Journal.
Work experience in the area of Human genomics/Next Generation Sequencing data analysis/Big data genomics would be preferred.
Application link:

https://sgrh.com/joblist

Post Code: 2023, 2024

#NBGN21

www.nbgn21conference.com

More at http://www.hiit.fi/postdoc-call-2013

Classificier of reads from metagenomic sequencing experiments.

•  Kawulok, J., Deorowicz, S., CoMeta: Classification of Metagenomes Using k-mers, PLOS ONE, 2015; 10(4):1–23,

CoMSA

Compressor of multiple sequence alignments of proteins.

•  Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A., CoMSA: compression of protein multiple sequence alignment files, Bioinformatics, 2019; 35(2):22–234,

DSRC

Compressor of sequencing reads.

•  Roguski, L., Deorowicz, S., DSRC 2: Industry-oriented compression of FASTQ files, Bioinformatics, 2014; 30(15):2213–2215,
•  Deorowicz, S., Grabowski, Sz., Compression of DNA sequences in FASTQ format, Bioinformatics, 2011; 27(6):860–862,

FAMSA

Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).

•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., FAMSA: Fast and accurate multiple sequence alignment of huge protein families, Scientific Reports, 2016; 6(33964):

FaStore

Compressor of FASTQ files.

•  Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S., FaStore - a space-saving solution for raw sequencing data, Bioinformatics, 2018; 34(16):2748–2756,

FQSqueezer

Experimental high-end compressor of FASTQ files.

•  Deorowicz, S., FQSqueezer: k-mer-based compression of sequencing data, Scientific Reports, 2020; 10(578):

GDC

Compressor of collections of genome sequences.

•  Deorowicz, S., Danek, A., Niemiec, M., GDC 2: Compression of large collections of genomes, Scientific Reports, 2015; 5(11565):1–12,
•  Deorowicz, S., Grabowski, Sz., Robust relative compression of genomes with random access, Bioinformatics, 2011; 27(21):2979–2986,

GTC

Genotype databases compressor with support for fast queries.

•  Danek, A., Deorowicz, S., GTC: how to maintain huge genotype collections in a compressed form, Bioinformatics, 2018; 34(11):1834–1840,

GTShark

Genotypes compressor.

•  Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, Bioinformatics, 2019; 35(22):4791–4793,

KMC

Memory frugal k-mer counter.

•  Kokot, M., Długosz, M., Deorowicz, S., KMC 3: counting and manipulating k -mer statistics, Bioinformatics, 2017; 33(17):2759–2761,
•  Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A., KMC 2: Fast and resource-frugal k-mer counting, Bioinformatics, 2015; 31(10):1569–1576,
•  Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz., Disk-based k-mer counting on a PC, BMC Bioinformatics, 2013; 14():Article no. 160,

Kmer-db

Tool for estimation of evolutionary distances in a collection of genomes.

•  Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A., Kmer-db: instant evolutionary distance estimation, Bioinformatics, 2019; 35(1):133–136,

MuGI

Index allowing queries for a collection of multiple genome sequences.

•  Danek, A., Deorowicz, S., Grabowski, Sz., Indexes of Large Genome Collections on a PC, PLOS ONE, 2014; 9(10):e109384,

ORCOM

Experimental compressor of sequencing reads.

•  Grabowski, Sz., Deorowicz, S., Roguski, L., Disk-based compression of data from genome sequencing, Bioinformatics, 2014; 31(9):1389–1395,

PgSA

Index allowing queries for a collection of sequencing reads.

•  Kowalski, T., Grabowski, Sz., Deorowicz, S., Indexing arbitrary-length k-mers in sequencing reads, PLOS ONE, 2015; 10(7):1–16,

QuickProbs

Multiple sequence alignment designed especially for GPU.

•  Gudys, A., Deorowicz, S., QuickProbs 2: towards rapid construction of high-quality alignments of large protein families, Scientific Reports, 2017; 7(41553):
•  Gudys, A., Deorowicz, S., QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors, PLOS ONE, 2014; 9(2):e88901,

RECKONER

Read error corrector.

•  Maciej Długosz, M., Deorowicz, S., RECKONER: read error corrector based on KMC, Bioinformatics, 2017; 33(7):1086–1089,

TGC

Compressor of collections of genomes given in Variant Call Format (VCF) files.

•  Deorowicz, S., Danek, A., Grabowski, Sz., Genome compression: a novel approach for large collections, Bioinformatics, 2013; 29(20):2572–2578,

VCFShark

Compressor of VCF files.

•  Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, biorxiv.org, 2020; ():

Whisper

Experimental mapper of whole genome sequencing data.

•  Deorowicz, S., Gudys, A., Whisper 2: indel-sensitive short read mapping, bioRxiv.org, 2019; :
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Whisper: read sorting allows robust robust mapping of DNA sequencing data, Bioinformatics, 2019; 35(12):2043–2050,
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Robust mapping of whole genome sequencing data, Poster at The Biology of Genomes Conference, 2017;

WALK-IN-INTERVIEW

Walk-in-test cum interview for selection to the following temporary assignments sanctioned under the DBT sponsored adhoc time bound research scheme entitled "Establishment of a Sub-DIC" will be held at CPCRl, Kudlu PO, Kasaragod District, Kerala -6711 24 on the date and time indicated against each:

Project Assistant

Qualification: Essential: Masters Degree in Bioinformatics / B.Tech Degree in Bioinformatics

Desirable: 1. Experience in the field of bioinformatics
2. M.Phil / Doctoral degree in the field

Date of interview 24.09.2013 at 10.00 a.m.

Trainee – 2 Posts

Essential: Masters Degree in Bioinformatics or B.Tech Degree in Bioinformatics.

Date of interview 25.09.2013 at 10.00 a.m.

Studentship – 2 Posts

Essential Final Year/Semester students of MSc Bioinformatics or B.Tech Bioinformatics

Date of Interview 25.09.2013 at 10.00 a.m.

The candidates fulfilling the above eligibility criteria for Item No.1 & II shall apply online and walk-in for a written test and interview at CPCRI, Kasaragod on the respective dates at 10.00 a.m. The candidates for Studentship should submit the application through their Head of the Department. They shall also bring with them a set of bio data and original certificates in proof of age, educational qualifications, experience etc. Candidates who fail to produce the original of the Degree/PO certificates OR provisional certificate will not be allowed to attend the test / interview. Those who are qualified in written test will only be permitted to attend the interview.

No TA will be paid for the journey for attending the interview.

Advertisement: http://www.cpcri.gov.in/images/images/opportunity/sep4_opp.pdf

Plants represent an untapped resource of natural bioactive compounds that significantly contribute to plant resilience to pathogens, herbivores, and abiotic stresses, and may be applied for medicine or crop protection. In this project, you will design and/or apply innovative omics integration strategies for genomics, transcriptomics, and metabolomics data, to discover plant specialized metabolite biosynthetic pathways and study their evolution. You will work together with the other PhD candidate in this project, which will entail a combination of algorithm development, greenhouse experiments, integrative omics analysis, and evolutionary genomics. Extensive local and international collaboration is foreseen, including possibilities for a foreign research visit as part of your PhD project.

The research is embedded within the chairs of Bioinformatics and Biosystematics. The projects will be (co-)supervised by Dr. Marnix Medema, Dr. Justin van der Hooft, Dr. Klaas Bouwmeester and Prof. Dr. Eric Schranz.

We ask

We are looking for two enthusiastic and complementary team players with all or a subset of the following skills:

a solid academic record (MSc) in bioinformatics, biology, or biotechnology
experience in computational omics analysis and proficiency in programming (in, e.g., Python)
at least basic to intermediate statistical and mathematical skills
demonstrable experience in working with next-generation sequencing data or with greenhouse experiments with plants
affinity with plant science, metabolism and/or biosynthetic pathways
you meet all the entry requirements of the WUR PhD programme.
More information

For more information about this position, please contact Marnix Medema, Associate Professor Bioinformatics, by email (marnix.medema@wur.nl).
For more information about the procedure, please contact vacaturemeldingen.psg@wur.nl.

An exciting opportunity exists for a highly motivated and enthusiastic bioinformatics researcher to work in the Exosome, Secretome and Systems Biology laboratory of Dr Suresh Mathivanan. This position is funded through the National Institutes of Health (NIH) USA, to study the role of extracellular RNA or ExRNA in intercellular communication.

The successful applicant will be involved in collaborative bioinformatics research with more than 30 American Universities/Institutes. The ExRNA consortium is a multi-institute USD 17 million funded program which has 5 primary aims: to understand the biogenesis of ExRNA (vesicles and non-vesicles), to explore the use of ExRNA in biomarker research, to establish a reference profile of ExRNA in various disease conditions, to explore the role of ExRNA in therapeutic purposes and to manage the generated data through a reference portal. The bioinformatics component is critical in managing and analysing the data generated by the entire consortium. The researcher is required to contribute to the management and perform the analysis of ExRNA data.

The candidate to succeed, you will possess:

Experience in the analysis and modelling of data, including the capacity to integrate data from a range of sources and of uneven quality.

Evidence of experience in research and of the ability to work effectively under limited supervision or independently.

A record of contribution to publications, conference papers and/or reports, or professional or technical contributions which provide evidence of research potential.

Completion of a doctoral degree in bioinformatics or biostatistics with a focus on transcriptomic data will be highly regarded.

Preference will be given to applicants with competence in programming (JavaScript, Perl/Python), any web-based applications (PHP, ZOPE) and relational databases (MySQL).

Closing date: 30 September 2013

Position Enquiries: Dr Suresh Mathivanan (s.mathivanan@latrobe.edu.au)

More at http://www.mathivananlab.org/

The bioinformatics chat is produced by Roman Cheplyaka and hosted by Roman and Jacob Schreiber.

Address of the bookmark: https://bioinformatics.chat/

More at http://pandeylab.igm.jhmi.edu/

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