BOL: Related items

Ragan Lab

Sun, 14 Jul 2013 12:03:43 -0500

Computational systems biology

Research Area:
breast cancer; pancreatic cancer; prostate cancer; gastrointestinal disorders; urohaemolytic disorders; staphylococcal diseases

Ron Milo Lab

Fri, 23 Aug 2013 03:22:37 -0500

This research group brings the tools of systems biology to bear on the grand challenges of sustainability. The lab members and I are passionate about trying to understand the cellular highways of energy and carbon transformations known as central carbon metabolism in quantitative terms. They employ a combination of computational and experimental synthetic biology tools.
Ron Milo Lab research efforts are the culmination of three directions:
(1) Understanding the structure and logic of central carbon and energy metabolism in quantitative terms
(2) Synthetic metabolic pathways for carbon fixation
(3) Novel tools facilitating accurate, accessible and collaborative quantitative cell biology

http://www.weizmann.ac.il/plants/Milo/index.php

Landry Lab

Thu, 17 Jul 2014 14:33:57 -0500

EVOLUTIONARY AND INTEGRATIVE CELL BIOLOGY

Our research is at the crossroad between cell biology, ecological genomics, systems biology, molecular evolution and population genetics. We study the architecture and evolution of protein and signalling networks.

More at http://landrylab.ibis.ulaval.ca/

Postdoctoral Researcher in Cancer Systems Biology

Mon, 12 Jan 2015 01:44:11 -0600

Postdoctoral Researcher in Cancer Systems Biology
Department of Oncology, Old Road Campus Research Building, Roosevelt Drive, Oxford
Grade 7: £30,434 - £37,394 with a discretionary range to £40,847 p.a.
Applications are invited for a Postdoctoral Researcher in Cancer Systems Biology to join a rapidly developing Bioinformatics Research Core group headed by Dr Anastasia Samsonova. The purpose of the role is to develop and deliver integrative approaches to dissect the complexity of cancer as a genomic disease. The research will focus on development and application of effective strategies for mining and integration of complex human *omics datasets and clinical/phenotypic data in cancer studies.

The role sits at the critical interface between genetics and cancer systems biology, and would suit a candidate who is interested in developing a career at the confluence of Statistics/Data Mining/Machine Learning and Biology. Ideally, you will have experience in development of analytical approaches to high-throughput and multivariate data mining and integration gained through a PhD (or equivalent) in a quantitative subject (eg mathematics, statistics, physics, engineering or computer science).

Experience of statistics and/or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing complex *omics data sets. You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should be able to organise and prioritise your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as applied mathematics, statistics, computer science and medicine.

This is a full-time post, fixed-term until 31 March 2017. For informal enquiries, contact Dr Anastasia Samsonova (bioinformatics@oncology.ox.ac.uk).

All applicants must complete a short application form and upload a CV and supporting statement.

The closing date for applications is 12.00 noon on 26 January 2015.

More at https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form

SYSTEMS BIOLOGY APPROACH TO MODEL INFLAMMATION IN HUMAN (2).pptx

ROSHNI — Thu, 17 Oct 2013 00:54:13 -0500