|CCL 17.06.06 Computational Chemical Biologist|
From: jobs at ccl.net (do not send your application there!!!)
To: jobs at ccl.net
Date: Tue Jun 6 09:24:36 2017
Subject: 17.06.06 Computational Chemical Biologist
The Computer-Aided Drug Discovery (CADD) team in Cambridge, Mass (USA) brings together diverse skill sets in helping NIBR discovery teams validate and drug new targets. We are seeking a unique computational scientist to complement the team with the skills, experience and passion to extract new knowledge and disruptive insights from the large and rich body of data collected by the one of the worlds oldest pharmaceutical companies. Working with a wide variety of multi- disciplinary scientists, you will help devise creative solutions to drug discovery problems and innovative paths to new medicines. Summary of duties: - Collaborate with interdisciplinary project teams to drive effective decision-making from target identification through candidate nomination by mining and developing predictive models using high-content and time-resolved screening data, including imaging. - Drive hypothesis generation to result in higher clinical success rates for programs utilizing small molecules peptides, RNAs, protein degradation, molecular glues, transient covalent inhibitors and kinetic stabilization of drug-target complexes. - Develop and apply innovative computational approaches to predict biological activity profiles of small molecules and peptides utilizing proteochemometrics, quantitative chemogenomics, computational metabolomics, computational systems biology, computational epigenomics, etc. - Keep abreast of scientific literature and interact with internal and external scientists to integrate biological insights into lead characterization and screening efforts. - Perform experimental work related to project objectives and reports laboratory activities, fully responsible for adherence to Novartis global standards e.g. quality, safety, data security, productivity, innovativeness, timelines and cost effectiveness. Job Qualifications Education: Advanced degree in computational chemistry, computational biology, computational chemical biology, or related field. PhD strongly preferred. Candidates with an experimentalist background and strong computational experience are also encouraged to apply. Experience: - 3-5 years of experience with general machine learning (use to build AI systems). - Programming experience (R, Python, Matlab, Java). - Experience using machine learing libraries, such as scikit-learn TensorFlow and Theano - Strong publication history in peer-reviewed journals. Skills and Abilities: - Good listener. Strong, concise, and consistent written and oral communication. - Knack for communicating stories through data visualizations. - Strong statistical foundation with broad knowledge of deterministic and probabilistic statistical methods. - Familiar with the foundational concepts in molecular biology, pharmacology or medicine. - Experience with NGS, proteomics, and other high-throughput assays a plus. - Provide leadership for ad-hoc data analysis, visualization and statistical support throughout the organization - Working knowledge of medicinal chemistry and drug discovery. - Proven ability to collaborate with others.
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