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BACKGROUND
At Eisai, satisfying unmet medical needs and increasing the benefits healthcare provides to patients, their families, and caregivers is Eisai's human health care (hhc) mission. We're a growing pharmaceutical company that is breaking through in neurology and oncology, with a strong emphasis on research and development. Our history includes the development of many innovative medicines, notably the discovery of the world's most widely-used treatment for Alzheimer's disease. As we continue to expand, we are seeking highly-motivated individuals who want to work in a fast-paced environment and make a difference. If this is your profile, we want to hear from you.
Translational Discovery group in Human Biology Integration covers oncology preclinical and clinical translational research to accelerate clinical development of candidate drugs and to enable identification of novel targets. Data science, computational biology and bioinformatics are a fundamentally important core discipline and integral part of the Translational Discovery group. Data scientists play a key role in leveraging internal and external cancer genomics and pharmacogenomics data for developing new breakthrough oncology drugs, with a sharp strategic focus on employing entrepreneurial collaborative and business models to accelerate delivery of innovative medicines that address unmet patient needs.
SUMMARY
We are seeking a highly motivated data scientist to join the Translational Discovery group. This person will be responsible for performing hands-on exploratory and regulatory related biomarker analysis, large-scale genetic, genomic, and other 'omic analyses, with a primary goal of identifying and validating targets and biomarkers in preclinical studies and clinical trials for oncology. More specifically, this person will participate the design of genomic studies in preclinical and clinical research, implement cutting-edge informatics and statistical methods and tools to analyze the data including WGS/WES/targeted sequencing, RNAseq, proteomics data, metabolomics data, etc, and perform integrative analysis of genomic data and available clinical data in clinical trials. Furthermore, the individual will leverage external cancer genomic and pharmacogenomics data, and oncology real-world data (RWD) to integrate with Eisai internal data for biomarker analysis. All analysis work will be documented and will follow best practices for enabling reproducible research.
PRINCIPAL DUTIES & RESPONSIBILITIES
- Perform data analysis activities including cleaning, handling, integration, and analysis of biomarker data generated in clinical trials, including WES, RNA sequencing, serum proteins, and other data types to identify biomarkers correlated with clinical endpoints.
- Perform data analysis activities integrating internal and external multi-scale data generated from cell lines, model organisms, and human subjects, including genetic, genomic data, functional data, phenotypic data, and RWD to inform novel targets, combination strategies, or novel cancer indications for oncology assets that are currently under development.
- Analyze large-scale analysis-ready datasets to answer specific focused questions of relevance to project teams.
- Provide appropriate visualization and interpretation of results in preclinical and clinical data to support decision making on drug development projects.
- Contribute to clinical biomarker study design to generate statistically meaningful information.
- Contextualize findings from internal experiments and generate hypotheses for new internal experiments by analyzing and interpreting externally available data.
- Prepare and track documentation including analysis plans, result reports, and progress reports.
REQUIREMENTS
- Ph.D. degree in Biomedical Sciences, Bioinformatics, Computational Biology, or closely related field. 2-5 years of post-graduate experience in hands-on cancer genomic data analysis.
- Must have analytic and statistical skills to conduct analysis of WGS/WES, transcriptomic, proteomic and epigenetic data. Must have experience in oncology clinical outcome analysis.
- Must have a good understanding of human biology. Experience in cancer research is highly desirable. Must demonstrate good understanding of drug discovery requirements and processes.
- Must have strong organizational skills and ability to prioritize work.
- Must have excellent communication skills and the ability to act on cross-disciplinary teams; must have demonstrated ability in scientific publications.
- Must have experience with R, Unix/Linux systems and AWS cloud computing. Additional experience with languages/software including Python, SQL, Spotfire is strongly preferred.
POLICY
Eisai is an equal opportunity employer and as such, is committed in policy and in practice to recruit, hire, train, and promote in all job qualifications without regard to race, color, religion, gender, age, national origin, citizenship status, marital status, sexual orientation, gender identity, disability or veteran status. Similarly, considering the need for reasonable accommodations, Eisai prohibits discrimination against persons because of disability, including disabled veterans.
Eisai Inc. participates in E-Verify. E-Verify is an Internet based system operated by the Department of Homeland Security in partnership with the Social Security Administration that allows participating employers to electronically verify the employment eligibility of all new hires in the United States. Please click on the following link for more information:
Right To Work (https://us.eisai.com/-/media/Files/Eisai/RightToWorkPoster.pdf?la=en)
E-Verify Participation (https://us.eisai.com/-/media/Files/Eisai/EVerifyParticipationPoster.pdf?la=en)
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October 10-12, 2024
Houston, TX, USA
https://icibm2024.iaibm.org
We are pleased to announce the 12th International Conference on Intelligent Biology and Medicine (ICIBM 2024), which will take place in Houston, TX, USA. ICIBM is a high-caliber conference that brings together eminent scholars with expertise in various fields of computational biology, systems biology, computational medicine, and experimentalists interested in the application of computational methods in biomedical studies. The purpose of the ICIBM is to provide a congenial atmosphere highly conducive to extensive discussion and networking. You are invited to submit papers and abstracts with unpublished, original work describing recent advances in all aspects of Bioinformatics, Intelligent Computing, Systems Biology, and Medical Informatics, including but not restricted to the following topics:
Bioinformatics:
- Genomics and genetics/epigenetics, including integrative & functional genomics, genome evolution, GWAS.
- Next-generation sequencing data analysis, 3D genome.
- Big data science including storage, analysis, modeling, visualization, and cloud.
- Precision medicine, translational bioinformatics, and medical informatics.
- Drug discovery, design, and re-purposing.
- Proteomics, and protein structure prediction, function, and interactions.
- Single-cell sequencing data analysis.
- Microbiome and Metagenomics.
Intelligent Computing and Data Science:
- Artificial intelligence, machine learning, deep learning, data mining, knowledge discovery.
- Large language model, foundation model, and computer vision in biomedical.
- Natural language processing, literature mining, semantic ontology, and health informatics.
- Neural computing, kernel methods, feature selection/extraction.
- Evolutionary computing, swarm intelligence / optimization, ensemble methods.
- Artificial life and artificial immune system.
- Biomedical image analysis and processing.
Systems Biology:
- Modeling and simulation of biological processes, pathways, networks, and interactomes.
- Modeling of cellular and multi-cellular interaction systems.
- Multi-dimensional omics data integration.
- Synthetic biological systems.
- Metabolomics, microbiome, and lipidomics.
- Self-organization in living systems (cells, organisms, swarms, ecosystems, etc.).
Medical Informatics:
- Cohort discovery, EHR-based phenotyping, predictive modeling.
- Data quality assessment or validation.
- Clinical decision support solutions.
- Informatics to address disparities in health and health care.
- Interoperability (e.g., ontology, terminology, standards, and others).
- Machine learning for clinical applications, genome, and phenome analysis/associations.
- Mobile health and wearable devices.
- Human-computer interaction and human factors
Paper Submission and Publication:
Prospective authors are invited to submit unpublished work to ICIBM 2024. All papers and abstracts will be initially submitted through the EasyChair Conference System. Selected papers of the registered authors will be recommended to be published in special issues in the following journals, subject to additional editorial approval and expected additional review by each journal: Patterns (impact factor: 6.5), Computational and Structural Biotechnology Journal (CSBJ, impact factor: 6.0), International Journal of Molecular Sciences (IJMS, impact factor: 5.6), Quantitative Biology (impact factor 3.1), Information (impact factor 3.1), Cancers (impact factor 5.2).
Abstract Submission:
Conference participants are invited to submit abstracts to ICIBM 2024. Abstract submitted to the conference should be formatted using the Abstract Template. The abstract body should be no more than 400 words. We welcome submissions of highlight papers that have been recently published or accepted for publication. In this case, the abstract should include a complete reference to the published paper. A group of experts will evaluate the submissions and select the abstracts to be presented orally or as a poster. Please submit your abstract to icibm2024.abstract[at]gmail.com.
Travel Awards:
The Travel Award, which pending on a grant application, is to encourage young scientists in training, including graduate, undergraduate and high school students, as well as postdoctoral fellows. Specific consideration will be given to qualified applicants from underrepresented populations, minority institutes, female trainees, or those who needs special financial support to attend ICIBM 2024.
IMPORTANT DATES
Deadline for original paper submission: July 5 (Fri), 2024
Notification to authors of papers: August 23 (Fri), 2024
Deadline for abstract submission: August 30 (Fri), 2024
Conference early registration opens: June 20 (Thurs), 2024
Conference early registration deadline: September 10 (Tues), 2024
Deadline for travel award application: September 11 (Wed), 2024
Conference regular registration: September 11 – October 10, 2024
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DESCRIPTION
Join Our Team at Dr. Gu's Lab, Versiti Blood Research Institute, Milwaukee, WI.
Are you a driven and passionate individual with expertise in machine learning, bioinformatics, biostatistics, genomics, genetics, computational biology, or cancer biology? If so, we invite you to become part of our dynamic team at Dr. Gu's lab at the Versiti Blood Research Institute in Milwaukee, WI. We are seeking a highly motivated Postdoctoral Fellow to contribute to groundbreaking research in the field of multi-omics data analysis, cancer biology, and biomarker discovery.
Position Overview:
As a Postdoctoral Fellow, you will have the unique opportunity to develop and implement cutting-edge machine learning algorithms and statistical models. These tools will be applied to unravel the complexities of multi-omics data, shedding light on the mechanisms underlying cancer biology (leukemia, lung, and kidney cancer) and facilitating the identification of early diagnostic and treatment biomarkers. Additionally, if you have an interest in experimental work, you will have the chance to gain valuable hands-on experience and training.
REQUIREMENTS
Education:
- Master's Degree required
- PhD required
- Equivalent degree required
Experience:
- 0-6 years of postdoctoral training required
- Proficiency in Python or R, ideally both
- Knowledge of biology, genomics, genetics, and Next Generation Sequencing data is a valuable asset.
WHY JOIN US
- Contribute to cutting-edge research in a collaborative and innovative environment.
- Access state-of-the-art resources and mentorship to support your career development.
- Work in a vibrant city with a rich cultural scene and a welcoming community.
HOW TO APPLY
If you are passionate about harnessing the power of data to advance our understanding of cancer biology and want to be part of a team dedicated to making a difference, we encourage you to apply.
To apply for this position, please submit your CV, a cover letter detailing your research interests and relevant experience and contact information for at least three references to tgu[at]versiti.org.
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BACKGROUND
GDIT is seeking an experienced Scientific Program Manager to lead our Scientific IT program, supporting a large biomedical research community for our customer with the National Institute of Allergy and Infectious Diseases (NIAID).
Our Scientific IT program is responsible for enabling High Performance Computing and its associated infrastructure across multiple locations, scientific applications and instrumentation, and ~40PB of data storage to include data archive and sharing services. This program serves as a customer-facing presence for the NIAID research community, providing a single point of support for new initiatives, ongoing projects, and scientific IT needs. In your role as a Scientific Program Manager, you will lead a multidisciplinary team responsible for delivering comprehensive scientific services to an end-user community of approximately 4500.
Under your leadership, you will be responsible for developing and implementing customer support policies and procedures with a focus on metrics driven execution to ensure that scientific and computational services are delivered to our client on time and efficiently. You will proactively identify areas for improvement, implement process enhancements, and drive efficiency for our scientific services portfolio. You will prioritize building relationships with researchers to understand their needs, solve challenges, and align our program to deliver value to support scientific research. You must be able to simultaneously manage various duties and obligations such as project and team management to ensure customer satisfaction while enhancing the caliber of services delivered.
RESPONSIBILITIES
- Provides day to day team management and oversight of project execution and service delivery for scientific infrastructure and scientific instrumentation teams. This includes delegating tasks, providing clear direction, and inspiring collaboration and teamwork.
- Accountable for the development and delivery of scientific IT services and capabilities, strategic planning, budgeting and forecasting, and customer outreach and engagement.
- Overseeing personnel management including staff recruitment, hiring, performance management, training, and mentoring.
- Ensures service delivery alignment with program and customer strategic goals by developing strategic roadmaps and tracking KPI's.
- Collaborates with internal and external resources to identify new service offerings to enable and advance scientific research. Develop plans and identifies resources required for implementation and execution.
- Facilitate regular discussions with researchers to understand needs and challenges.
- Provides transparent communications on project timelines, resource requirements, risk management, and status reporting across all organizational and technical boundaries.
- Provides oversight for critical incidents, coordinating with resolution parties and establishing effective communication between stakeholders for post incident reviews and after-action reporting.
REQUIREMENTS
- Masters and 5+ years experience or equivalent in a Science and IT related discipline
- 5+ years experience leading multiple computational science programs
- 5+ years experience in IT project management or development and delivery of scientific IT services
- Demonstrated experience leading multidisciplinary teams supporting operations and maintenance of computational science systems and applications
- Understanding of general workflows for scientific data generation, analysis, and reporting
- Understanding of challenges and approaches for large scale scientific data management
- Experience developing and aligning relationships with diverse stakeholders at all levels from scientists through senior leadership
- Experience providing accurate and regular reports to measure how deliverables align with the organization values and strategic objectives
PREFERENCES
- Education or experience in life or physical sciences
- Experience leading cross-functional teams including scientists and engineers
- Experience leading teams supporting engineering and administration of computational science infrastructure, including HPC and associated components
- Experience providing IT support for scientific instrumentation installation, configuration, operations, and troubleshooting
- Experience supporting large collections (hundreds) of shared applications, many of which are open source
- Familiarity with genomic analyses tools, workflows and data types
- Familiarity with Agile Scrum and/or Kanban methodologies
- Familiarity with principles and practices of ITIL to include incident management, problem management, service request management, change management, and service level management.
- Understanding of the National Institute of Standards and Technology (NIST) cybersecurity framework and Security Assessment and Authorization (SA&A) process
LOCATION
This position is primarily remote; however, you must reside within commuting distance to the client site in Rockville, MD and be able to be onsite at least 1x a week to meet contractual obligations and project needs. Possible travel to the Montana location.
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In a new Nature Communications article, researchers describe a genomic language model (gLM) capable of predicting protein co-regulation and function. The gLM, which was trained on millions of metagenomic scaffolds, has learned to interpret the language of genes, revealing the intricate dance of protein regulation and enzymatic functions. This approach is a leap forward in our understanding of the genomic blueprint and its regulatory networks.
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