Cheminformatics Analyst

We are a science and technology consulting company, based in RTP, NC, providing scientific consulting services to the US Federal Government, academic institutes, non-profit research organizations, and bio-pharmaceutical companies. We have a small team of PhD/Masters level scientists and informaticians and we are growing.

One of our main areas of expertise is biological data aggregation, mining and modeling. We utilize many types of biological, experimental and literature derived data to develop computational predictive models and data mining methodologies. We employ these methods in concert with other bioinformatics techniques to enable data and literature driven discoveries in support of life sciences research.

This is an exciting time to join our growing team. This position promises an impactful career in a fun and relaxed work environment. We provide a competitive compensation package including benefits.

Detailed position description is provided below:

Education

PhD or Masters (applicants with master’s degree must have 3+ years of related working experience) in Statistics/biomathematics, Cheminformatics, Computational Toxicology or related discipline.

Responsibilities
  • Provide computational toxicology and cheminformatics expertise for development and evaluation of new, revised, and alternative methods to identify potential hazards (e.g. chemicals) to human health and the environment, with a focus on replacing, reducing, or refining animal use.
  • Use statistical and computational methods to perform analysis of varied types of chemical and biological data. This may include use of Bayesian, machine learning or network based methodologies.
  • Participate in PBPK modeling, reverse toxicokinetics, adverse outcome pathway (AOP) analysis and other such data analysis activities using off the shelf or customized tools and methods.
  • Investigate statistical approaches for analysis of High Throughput Screening (HTS) data. Participate in collecting, quality control, normalization, dose response modeling and other such detailed analyses of specific HTS and/or ‘omics data sets.
  • Participate in group activities for data analysis methods development and deployment for scientific data integration approaches. Research, implement and test informatics and statistical techniques.
  • Provide quantitative, informatics and programming expertise towards development of data modeling tools, methods and analytical informatics approaches.
  • Interface with scientists in the fields of environmental health and toxicology to organize, analyze and model scientific data. Analysis may be focused on assessment of high throughput screening data, in-vitro assays or other such alternative methods.
Skills

The ideal candidate would have several of the following skills:

  • Thorough understanding of computational chemistry methods, algorithmic design and statistical concepts of data analysis is desired.
  • Track record of use and development of data mining, machine learning and/or artificial intelligence for predictive modeling.
  • Strong scripting and programming experience with R, Perl, Python or similar languages.
  • Candidates with experience with analysis of high throughput screening data using open source tools and algorithms and familiarity with public resources for toxicology data and data mining concepts are preferred.
  • Experience with customization of data analysis work flows and familiarity with data integration concepts.
  • Understanding of the use of alternative toxicology methods for reduction of animal studies in toxicology is preferred but not required.
  • A strong communicator who effectively adjusts to technical and non-technical audiences.
  • Able to prioritize and deliver results with a high emphasis on quality, technical rigor, and attention to detail.
  • Sound scientific proficiency, creativity, and independence in thought.
  • Able to integrate feedback in a professional manner and thrives in multidisciplinary teams with members with highly diverse backgrounds.
Your Role

You will have an opportunity to participate in one or more of the following:

  • Analysis of large quantities of scientific data using various open source or in-house methods.
  • Researching the most appropriate ways to tackle scientific data integration and data mining and participate in discussions with your colleagues.
  • Development of novel methods for data analysis, data modeling, data sharing, text mining or user interface development.
  • Performing analysis of toxicology, high throughput screening, ‘omics data using off the shelf methods, customized analysis work flows or in-house analysis routines.
  • Algorithm improvement, development of informatics work-flows, coding/software R&D and design and development of data mining or predictive modeling methodologies.
  • Discussions with your colleagues regarding project requirements, scientific analysis and interpretation.
  • Participation and presentation of work at national and/or international meetings.
  • Publication in peer reviewed scientific journals.
How to Apply

If you are interested in applying for this position please do the following:

  • Send your CV/Resume to jobs@sciome.com.
  • Refer to position title: Computational Chemistry Scientist.
  • Provide your contact information and a good time to reach you via phone.
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WORK WITH US

We are always looking for the brightest minds wanting to work in a small, well-integrated team environment to make a direct impact on important scientific projects as well as their own careers.

CURRENT OPENINGS

Bioinformatics Analysist

Sciome consults with leading researchers in the field and provides bioinformatics support for experiments generating ‘omics data from a variety of health and environmental projects. Sciome has an opportunity for a bioinformatics scientist to conduct analyses in support of a variety of genomics studies that investigate the role of genetic and environmental factors on biological systems. The candidate will have a unique chance to work with leading scientists having wide ranging perspectives on scientific issues and to progress his/her career in a growing organization.

The successful candidate will participate in the analysis of large, high-throughput ‘omics datasets such as those generated by next generation sequencing and microarray platforms via the application of bioinformatics and statistical methods. Projects may also include analyses of toxicological, environmental and other biological data types in addition to genomics data. Typical projects investigate changes in chromatin marks (ChIP-Seq, ChIP-Chip), gene expression (mRNA-Seq, Microarray), and the influence of genetic variations (SNPs, genetic rearrangements, etc.) in response to environmental stressors. Data analysis will be carried out using off the shelf bioinformatics analyses techniques as well as in house methodologies. Data management, analysis, interpretation, and documentation leading up to publications will be necessary for successful progression of projects.

Education

Masters or PhD degree in Bioinformatics / Computational Biology / Computer Science / Statistics or closely related field.

Key Responsibilities
  • Bioinformatics analysis of genomics data arising from next generation sequencing and microarray platforms. Specific data types include Exome-seq, ChIP-seq, ChIP-on-Chip, mRNA-seq, DNA-Seq and microarray gene expression or genotype data.
  • Perform statistical analysis of genomic datasets and participate in methods development while working with Sciome team members. Utilize appropriate off-the-shelf tools or in-house methods and keep up with the literature on rapidly evolving next generation sequence data analysis tool sets.
  • Contribute towards the management of large biological datasets and maintaining data analysis workflows as necessary for analysis of sequencing and microarray data.
  • Participate in drafting data analysis plans per project needs, perform bioinformatics analysis of the data, interpret results and communicate the results with clients and researchers.
  • Document analysis workflows and methods for further report generation and/or scientific publication in peer reviewed journals.
Desired Skillset

Experience with analysis of Exome-seq, DNA-Seq, ChIP-seq, ChIP-Chip, mRNA-seq and microarray datasets.

  • Understanding of the wide range of bioinformatics tools and methods for analysis of data originating from next generation sequencing and microarray platforms.
  • Experience with applying appropriate statistical and/or bioinformatics analyses to large molecular biological datasets.
  • Familiarity with statistical data analysis methods such as generalized linear and additive models, mixed effects models and other multivariate methods, Bayesian methods, power and sample size calculation, machine learning methods for genomics as well as computational biology methodologies for microarray, SNP, and next generation sequence data analysis.
  • Experience with the use of statistical packages in R and experience in scripting languages such as Perl, Python or Matlab.
  • Software coding experience in multiple languages is preferred.
  • Strong communication and writing skills in English are essential.
  • The ideal candidate will have a proven track record of scientific publication in the fields of bioinformatics, genomics and/or the life sciences.
  • Must be eligible to work in the U.S.
How to Apply
  • Please send your detailed CV via email to jobs@sciome.com.
  • Please refer to Senior Bioinformatics Scientist position and include your accurate contact information.

Software Developer

We are a science and technology consulting company, based in RTP, NC. We provide our scientific consulting services to the US Federal Government, Academic institutes, Non-profit research organizations, and Bio-pharmaceutical companies. We have a small team (PhD/Masters/Bachelors level scientists and developers) and we are growing!

One of our main areas of expertise is in biological data and text mining. In this domain, we specialize in developing computational methodologies for text and scientific literature mining which we implement in the form of desktop and web-enabled applications in order to solve real-world problems on behalf of our clients. In addition, we also employ these methods in concert with other bioinformatics techniques to enable data and literature driven discoveries in support of life sciences research.

We have an opening for a software engineer position. This is a new growth opportunity and it is a great time to join our growing team. This position promises an impactful career in a fun and relaxed work environment with flexible work hours. We provide a complete compensation package including competitive base salary, 401(k), medical, dental and disability coverage.

Detailed position description is provided below:

Responsibilities

As a member of our team you will be responsible for contributing to the design, implementation, testing and maintenance of several new and ongoing desktop and web applications. You will work with other scientists and engineers to:

  • Produce high quality code to ensure maintainability
  • Implement new features and contribute to the development of new and existing software products
  • Participate in design meetings and code reviews
Education
  • Bachelors in Computer Science (or related field) or relevant, related work experience
Basic Qualifications

The ideal candidate would have several of the following skills and experience:

  • At least 4 years of experience as a software engineer (Preferably Java)
  • Experience with relational databases (MySQL, SQL Server, etc.)
  • Familiarity with Object Oriented Programming with design and architecture patterns
  • User Interface design and development experience
  • Experience participating in high quality code and design reviews
Preferred Candidate Qualifications
  • ORM experience (Hibernate)
  • Spring framework
  • Desktop — Experience designing and developing desktop applications
  • Web — Experience designing and implementing web-enabled front ends
  • Relational database environments
  • Experience writing unit test cases (JUnit, NUnit, etc.)
  • Understands different software development methodologies
  • Past experience creating UML diagrams
  • Previous exposure to scientific applications and/or scientific data analysis
How to Apply

If you are interested in applying for this position please do the following:

  • Send your CV/Resume to jobs@sciome.com
  • Please refer to position title Software Engineer
  • Provide your contact information and a good time to reach you via phone

Scientist, Natural Language Processing

Sciome develops and deploys software solutions that leverage text-mining and natural language processing methodologies to identify, extract and integrate key scientific data and concepts from scientific publications in support of a variety of literature-driven research efforts, primarily in the domains of health and environmental science. The successful candidate will work as part of a diverse team, using their natural language processing and machine learning expertise to research, develop and integrate state-of-the-art text processing methods into our tools and analysis pipelines. In addition, the candidate will have a unique chance to work with leading scientists having wide ranging perspectives on scientific issues and to progress his/her career in a growing organization.

This is a great time to join our growing team. This position promises an impactful career in a fun and relaxed work environment. Detailed position description with technical details is provided below:

Education

Masters or PhD in Computer Science, Natural Language Processing, Computational Linguistics, Statistics, Library Science, Bioinformatics or related discipline.

Desired Skillset

The ideal candidate will have experience in several of the following areas:

  • Development and implementation of novel methods for data extraction from free text data, including named entity recognition, relation extraction, part of speech tagging, etc.
  • Development and implementation of methods for unsupervised identification of keywords and for detection of word similarity: latent semantic indexing, brown clustering, word2vec, etc.
  • Development and implementation of methods for topic modeling, document clustering and text summarization.
  • Design and coding of algorithms that can enable researchers to identify, categorize, prioritize and process large volumes of free-text scientific literature.
  • Experience with the key open source software resources in these domains.
  • Software coding experience in multiple languages is preferred.
  • Strong communication and writing skills in English are essential.
  • The ideal candidate will have a proven track record of scientific publication in the fields of text-mining and/or natural language processing.
  • Must be eligible to work in the U.S.
How to Apply
  • Please send your detailed CV via email to jobs@sciome.com.
  • Please include your accurate contact information.

Statistician

Sciome consults with leading researchers in the field and provides analytics support for experiments generating ‘omics data from a variety of health and environmental projects. Sciome has an opportunity for a Statistician to develop customized analysis tools in support of a variety of genomics studies that investigate the role of genetic and environmental factors on biological systems. The candidate will have a unique chance to work with leading scientists having wide ranging perspectives on scientific issues and to progress his/her career in a growing organization.

The successful candidate will apply novel and conventional statistical methods in the analysis of large, high-throughput ‘omics datasets such as those generated by next generation sequencing and microarray platforms. Typical projects investigate changes in key genetic activity indicators such as gene expression and chromatin marks in response to environmental stressors. Projects may also include analyses of toxicological, environmental and other biological data types in addition to genomics data. Data analysis will often need to be carried out using custom-built analysis models. Responsibilities include statistical support for the entire project lifecycle including: statistical model development, evaluation of the appropriateness of assumptions for proposed models, assessment of model goodness of fit, evaluation of model performance, interpretation of the results, and detailed documentation leading up to publications in the peer-reviewed scientific literature.

Education

Masters or PhD degree in Statistics / Mathematics or closely related field.

Key Responsibilities
  • Perform statistical analysis of genomics data arising from next generation sequencing and microarray platforms. Specific data types include Exome-seq, ChIP-seq, ChIP-on-Chip, mRNA-seq, DNA-Seq and microarray gene expression or genotype data.
  • Perform statistical analysis of genomic datasets and participate in methods development while working with other Sciome team members.
  • Participate in drafting data analysis plans per project needs; perform statistical analysis of the data; interpret results and communicate the results with clients and researchers.
  • Document analysis workflows and methods for further report generation and/or scientific publication in peer-reviewed journals.
Desired Skillset
  • Demonstrated ability to select appropriate statistical techniques given a data analysis problem.
  • Demonstrated willingness to learn new techniques and an ability to work independently in a fast-paced environment.
  • Understanding of the wide range of statistical analysis techniques for analysis of data originating from next generation sequencing and microarray platforms.
  • Experience with applying appropriate statistical and/or bioinformatics analyses to large molecular biological datasets.
  • In-depth knowledge of core statistical principals and various area of statistical sciences such as generalized linear and additive models, mixed effects models and other multivariate methods, Bayesian methods, power and sample size calculation, dimensionality reduction etc.
  • Familiarity with commonly used machine learning methods including support vector machines, random forests, deep learning etc. for signal enhancement and classifier development.
  • Experience with the use of statistical packages in R, SAS BASE/STAT/IML and Sci-kit
  • Scientific programming experience using scripting languages such as Perl, Python is preferred.
  • Strong communication and writing skills in English are essential.
  • The ideal candidate will have a proven track record of scientific publication in biostatistics, bioinformatics, genomics and/or the life sciences.
  • Must be eligible to work in the U.S.
How to Apply
  • Please send your detailed CV via email to jobs@sciome.com.
  • Please refer to Statistician position and include your accurate contact information.