https://www.ncbi.nlm.nih.gov/research/groups/koonin/

CRI-FEM hosts GMPF, an International PhD Program in Genomics and Molecular Physiology of Fruit Crops and Fox-Lab, an international initiative in forest and wood research.
4 positions in high throughput computational metagenomics and systems biology of natural products - deadline September 30th, 2013

To support interdisciplinary research, CRI-FEM has established the Computational Biology Centre (CBC).

The mission of CBC is to develop systems-level integrative approaches connecting genotype to phenotype with a special focus on genome-wide analyses and next generation sequencing technologies.

CRI-FEM is seeking to attract 4 high calibre scientists in the areas of high throughput computational metagenomics and systems biology of natural products.

Here below the list of the 4 positions:

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Metagenomics-screening-and-characterization-of-bioactive-microbial-compounds-130_CRI_MSC

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Modeling-transcriptional-control-programs-at-a-genome-wide-scale-131_CRI_TCP

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Technologist-in-Purification-of-plant-bioactive-molecules-from-complex-matrixes-132_CRI_PBM

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Researcher-in-Methods-for-algorithmic-and-integrative-genomics-for-metagenomics-134_CRI_AIG

For more information on the CBC or informal inquiries on the advertised positions please contact Dr Duccio Cavalieri (e-mail duccio.cavalieri@fmach.it).

#rasalsi #rasa In our Industrial program you will get Knowledge on RNA Seq, CHIP Seq,

Batch Starts From 18^th November 2019

#hurryup #registernow #enquirenow The primary goal of the industrial training program is to provide students with necessary skills making with employable. RASA LSI trains students with the enhanced skills required for them to excel in jobs in biotechnology, pharmaceuticals, BioIT and related industry sectors. At Rasa you will  learn from industry leaders how to apply these skills in life science & have a command over software developing process  by using various methodologies. For Registration visit us on: https://www.rasalsi.com/index.php/front-page/industrial-training/

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential

Computational and systems biology: studying the interplay between network topology and biological function, disease, and evolution in molecular (e.g., protein-protein interaction) networks.

Computational chemistry: protein folding; computational drug discovery and design.

Synthetic biology.

More at http://www.cse.nd.edu/~tmilenko/index.html

The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology
Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms
Genomic signatures of adaptation to a parasitic life-style

More at https://edanchin.org/

Xiaole Shirley Liu (lead instructor)
Joshua Starmer
Martin Hemberg
Ting Wang
Feng Yue

Ming Tang
Yang Liu
Jack Kang
Scarlett Ge
Jiazhen Rong
Phillip Nicol
Maartin De Vries

We thank many colleagues in the community, who helped Dr. Liu in prepare the STAT115/215 BIO/BST282 course over the years. 

Address of the bookmark: https://liulab-dfci.github.io/bioinfo-combio/

Models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer. Application to breast, ovarian, colorectal, pancreatic and skin cancer.

Statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects; integration of genomic information across technologies; cross-study validation of genomics results.

Statistical methods for comparative effectiveness research: comprehensive models for lifetime history of chronic disease outcomes; Bayesian meta-analysis; Bayesian causal inference; decision analysis.

Bayesian modeling and computation: multilevel models; decision theoretic approaches to inference; sequential experimental design and their application to adaptive and multistage studies in clinical and epidemiological research.

http://bcb.dfci.harvard.edu/~gp/index.html

http://scholar.google.com/citations?user=OlpYP3UAAAAJ&hl=en

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040