Position 1: Traineeship
Monthly fellowship (in rupee): 5,000/-
No. of vacancies: Two
Required Qualification: First Class M.Sc Bioinformatics/ Biotechnology/ Botany

Position 2: Studentship
Monthly fellowship (in rupee): 5,000/-
No. of vacancies: Two
Required Qualification: M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.

Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.

Interested candidates may appear for walk-in-interview on 15th May 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am.

More at http://jntbgri.res.in/news/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics/

Department of Genetics

University of Delhi South Campus

NEW DELHI – 110 021

WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT & LAB / FIELD ATTENDANT

1 Research Scientist (RS) – 3

DBT, Ph. D.

Experience on DNA Markers, plant genome mapping and bioinformatics

Salary: 60,000 (Consolidated) + 5% annual increment

Date and time: 25.06.2015 at 10:30 AM

These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’

The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.

Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.

No TA/DA will be paid for attending the interview.

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(ABT/DIC/01/2014 (No. AAU/ABT/DIT/Advt. 01/2015/111 Dtd. 19-05-2015)

Walk in interview for the following position will be held on 6th June, 2015 at 10.00AM in the Office Chamber of the undersigned. Candidates may appear for the interview with bio-data, reprints / publication / thesis etc and passport size photographs, original and attested copies of all testimonials etc, which must be presented at the time of interview. The applicants may submit their resume in advance tomkmodi@aau.ac.in.

Research Associate

Ph.D. in Biotechnology/ Bioinformatics. Or

Masters degree in Biotechnology/Bioinformatics with minimum 3(three) years research experience

Desirable : Experience in Bioinformatics as evidenced from published research

Rs 36,000+HRA for the 1st two years and 38,000+HRA for the 3rd year.

Senior Research Fellow

Master Degree in Biotechnology/ Bioinformatics. With 2 (two) years Experience in Bioinformatics as evidenced from Course work/ Diploma/Published research

Rs 28,000+HRA for NET qualified candidate/Professional degree holder

Rs 18,000+HRA for non-NET qualified general degree holder

Junior Research Fellow

Master Degree in Biotechnology/ Bioinformatics/Computer Science/Computer Application

Desirable: Experience in Bioinformatics as evident from Course work/ Diploma/Published research

Rs 25,000+HRA for NET qualified candidate/Professional degree holder

Rs 16,000+HRA for non-NET qualified general degree holder

Note: Term and conditions will be as per the DBT, Govt of India guidelines.

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Applications are invited for the post of Senior Research Fellow- SRF (1) and Junior Research Fellow- JRF (1) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong.

Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite.

For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by atleast one good publication.

For JRF position, freshers can also apply.

Stipend: As per SERB norms.

Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 20.06.15. The hard copy is not required. The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com

Advertisement: http://www.nehu.ac.in/Advertisements/BiochemSERB_Advt_020615.pdf

Following are the list of Ancestral /sequence/ reconstruction (ASR) tools: 

inferCars

Reconstructs contiguous regions of an ancestral genome. Given information about adjacencies between conserved segments in each modern species, our goal is to infer segment order in the ancestral genome. To get a clean and precise statement of the problem, we formalize it using graph theory. We develop an algorithm that identifies a most parsimonious scenario for the history of each individual adjacency, although the whole-genome prediction is not guaranteed to optimize traditional measures like the number of breakpoints. We introduce weights to the graph edges to model the reliability of each adjacency.

ANGES:reconstructing ANcestral GEnomeS maps

A suite of Python programs that allows reconstructing ancestral genome maps from the comparison of the organization of extant-related genomes. ANGES can reconstruct ancestral genome maps for multichromosomal linear genomes and unichromosomal circular genomes. It implements methods inspired from techniques developed to compute physical maps of extant genomes.

Cocos

Constructs phylogenies of multi-domain proteins. With a given species tree and domain phylogenies, the procedure infers the composition of ancestral multi-domain proteins. Cocos implements and extend a suggested algorithmic approach by Behzadi and Vingron in an easy-to-use program. Such method could be applied to reconstruction of partial homologous units such as bacterial operons or protein complexes.

MySSP

Constructs an initial DNA sequence at the root of the tree and simulates evolution across the tree using a variety of common models of DNA evolution. MySSP is a program for the simulation of DNA sequence evolution across a phylogenetic tree. It is designed for large-scale studies, including simulation of multiple replicates and outputs sequences into NEXUS, MEGA, or FASTA formats. MySSP has a fairly simple graphical user interface (GUI) for basic use, but also has a specialized batch script interpreter to allow for more complicated or large-scale simulations.

PARANA: Parsimonious Ancestral Reconstruction And Network Analysis

Performs parsimony based inference of ancestral biological networks. Given multiple extant networks and phylogenetic information relating extant nodes, PARANA finds a parsimonious set of ancestral interaction events (edge gains and losses) which explain the extant networks. The framework adopted by PARANA is able to represent network evolution under models that support gene duplication and loss and independent interaction gain and loss. The method works on both directed and undirected networks and can incorporate asymmetric interaction gain and loss costs. In contrast to previous approaches, PARANA does not require knowing the relative ordering of unrelated duplication events and thus, works on phylogenetic trees even where branch lengths are not provided.

GapAdj: Gapped Adjacencies

A synteny-based method that is flexible enough to handle a model of evolution involving whole genome duplication events, in addition to rearrangements, gene insertions, and losses. Ancestral relationships between markers are defined in term of Gapped Adjacencies, i.e. pairs of markers separated by up to a given number of markers. It improves on a previous restricted to direct adjacencies, which revealed a high accuracy for adjacency prediction, but with the drawback of being overly conservative, i.e. of generating a large number of contiguous ancestral regions (CARs).

ANCESTOR

A web server allowing one to easily and quickly perform the last three steps of the ancestral genome reconstruction procedure. Ancestors implements several alignment algorithms, an indel maximum likelihood solver and a context-dependent maximum likelihood substitution inference algorithm. The results presented by the server include the posterior probabilities for the last two steps of the ancestral genome reconstruction and the expected error rate of each ancestral base prediction.

ProCARs

Reconstructs ancestral gene orders as contiguous ancestral regions (CARs) with a progressive homology-based method. ProCARs runs from a phylogeny tree (without branch lengths needed) with a marked ancestor and a block file. This homology-based method is based on iteratively detecting and assembling ancestral adjacencies, while allowing some micro-rearrangements of synteny blocks at the extremities of the progressively assembled CARs. The method starts with a set of blocks as the initial set of CARs, and detects iteratively the potential ancestral adjacencies between extremities of CARs, while building up the CARs progressively by adding, at each step, new non-conflicting adjacencies that induce the less homoplasy phenomenon. The species tree is used, in some additional internal steps, to compute a score for the remaining conflicting adjacencies, and to detect other reliable adjacencies, in order to reach completely assembled ancestral genomes.

FastML

A user-friendly tool for the reconstruction of ancestral sequences. FastML implements various novel features that differentiate it from existing tools: (i) FastML uses an indel-coding method, in which each gap, possibly spanning multiples sites, is coded as binary data. FastML then reconstructs ancestral indel states assuming a continuous time Markov process. FastML provides the most likely ancestral sequences, integrating both indels and characters; (ii) FastML accounts for uncertainty in ancestral states: it provides not only the posterior probabilities for each character and indel at each sequence position, but also a sample of ancestral sequences from this posterior distribution, and a list of the k-most likely ancestral sequences; (iii) FastML implements a large array of evolutionary models, which makes it generic and applicable for nucleotide, protein and codon sequences; and (iv) a graphical representation of the results is provided, including, for example, a graphical logo of the inferred ancestral sequences.

maxAlike

Reconstructs a genomic sequence for a specific taxon based on sequence homologs in other species. The input is a multiple sequence alignment and a phylogenetic tree that also contains the target species. For this target species, the algorithm computes nucleotide probabilities at each sequence position. Consensus sequences are then reconstructed based on a certain confidence level.

MLGO: Maximum Likelihood for Gene Order Analysis

A web tool for the reconstruction of phylogeny and/or ancestral genomes from gene-order data. MLGO was designed for analysis of large-scale genomic changes including not only rearrangements but also gene insertions, deletions and duplications. MLGO can be used to infer a phylogeny from genome rearrangement and gene order data, and can also obtain an estimation of ancestral genomes, given an input tree. MLGO takes the advantage of binary encoding on gene-order data, supports a fairly general model of genomic evolution (rearrangements plus duplications, insertions, and losses of genomic regions), and successfully accommodates itself into the framework of maximized likelihood.

Image Reference : Wiki

Monthly fellowship (in rupee): 5,000/-

Traineeship

First Class M.Sc Bioinformatics/ Biotechnology/ Botany

Studentship: 5,000/-

M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.

Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.

Interested candidates may appear for walk-in-interview on 16th June 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am

More at http://www.jntbgri.in/jntbgri/news/File0001.pdf

Eligibility : M Phil / Phd, MSc

Location : Delhi

Last Date : 27 Jun 2015

Hiring Process : Walk - In
Indian Agricultural Statistics Research Institute (IASRI) - Job DetailsDate of posting:03 Jun 15

Research Associate Statisticsjob position in Indian Agricultural Statistics Research Institute (IASRI)
on purely contractual temporary basis

Project : “ICAR-Network Project of Transgenic in Crops”

Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience.

No.of Post: 01

Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.

Age Limit : 40 years
How to apply

Walk-in-interview will be held on 27th June 2015, 10.30 A.M at IASRI, Pusa, New Delhi

More at http://iasri.res.in/employment/employment.htm

Starting 15th July 2015, the position relates to a project specifically for in silico drug docking, screening, design, optimisation and linkage with active chemists.

Experience in many docking softwares and operating systems is essential.

Additional experience in bioinformatics and computational biology tools will be useful.

Submit curriculum vitae to: sb.icgeb@gmail.com

Closing date: 5 July 2015

Job Description

The Global Trait Discovery Informatics (GTDI) group located at the DuPont Knowledge Centre (DKC), Hyderabad, India is currently seeking applications for a highly motivated computational biologist. The GTDI group contributes to research programs in plant biotechnology at the DKC as well as across research centers located in DuPont Pioneer, Johnston, Iowa and at the DuPont Experimental Station in Wilmington, Delaware.

We are looking for candidates who have experience in analysis of high-throughput -omics datasets. The researcher will be primarily responsible for analyzing diverse -omics datatypes, such as transcriptomics, proteomics and metabolomics and actively contribute towards building streamlined solutions.

The candidate will be part of a diverse team of experimental biologists, computational biologists and software developers. A critical aspect of this position involves working with global teams across multiple locations and will require effective project coordination and communication skills. This is an exciting opportunity for candidates with strong data driven skills, who want to work at the interface of computational and experimental biology and contribute towards scientific discovery.

Responsibilities

·Integrate and analyze multiple datatypes in the context of experimental observations with a goal towards formulating testable hypothesis.

·Understanding the research questions from experimental biologists and formulate relevant in silico analyses.

·Establish and implement systematic analysis workflows starting from processing of raw data to biological interpretation.

·Critically analyze a wide variety of experimental data with a view to solving the underlying research questions.

·Identify and generate datasets for scientific testing and evaluation of algorithms.

Qualifications

PhD in computational biology, bioinformatics, population genetics, complex systems, computer sciences or any relevant physical or mathematical sciences, with experience in analyzing diverse -omics datasets.

Job Qualifications

Qualifications

PhD in computational biology, bioinformatics, population genetics, complex systems, computer sciences or any relevant physical or mathematical sciences, with experience in analyzing diverse -omics datasets.

More at http://careers.dupont.com/jobsearch/job-details/research-scientist/006077W-01/