Associate Principal Scientist Computational Oncology (Hybrid)

Job Description

Our company in the United States and Canada, is a global health care leader with a diversified portfolio of prescription medicines, vaccines and animal health products. The difference between potential and achievement lies in the spark that fuels innovation and inventiveness; this is the space where our company has codified its legacy for over a century. our company's success is backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.

Our company is on a quest for cures and is committed to being the world's premier, most research-intensive biopharmaceutical company. Today, we're doubling down on this goal. Our company's Research Laboratories is a true scientific research facility of tomorrow and will take our company's leading discovery capabilities and world-class small molecule and biologics R&D expertise to create breakthrough science that radically changes the way we approach serious diseases.

The Data, AI, and Genome Sciences department is looking for a passionate and talented computational biologist to join our Translational Genome Analytics research team based in South San Francisco, CA. In this role, you will design and apply systematic machine learning and network-based approaches to elucidate molecular mechanisms of disease progression and drug response to drive target discovery and drug development efforts to impact our rapidly growing oncology portfolio. You will have the opportunity to collaborate with cross-functional teams of computational biologists, data scientists and bench scientists in Discovery Oncology.

Oncology research at our company is driven by a deep interest in the biology of tumor and its microenvironment, and how diverse points of intervention can be combined to achieve ever higher rates of durable response and patient overall survival.

In This Exciting Role, You Will

• Contribute to multiple stages of Oncology drug discovery to decode genetic dependencies and identify targetable cell-surface antigens by interrogating high-throughput assays, including genomics, transcriptomics and proteomics datasets.

• Leverage cutting-edge AI/ML and network-based approaches to elucidate multiscale cellular and disease mechanisms underlying drug response and resistance

• Integrate large internal and public biological data sets including Next Generation Sequencing (NGS) data (e.g. RNA-Seq, Perturb-Seq, single cell RNA-Seq, WGS, CRISPR) as well as rich compound screening data (e.g. PRISM, Sanger, MIX-seq) to inform target prioritization and drug combinations

• Collaborate with experimental scientists across functions to characterize novel targets coming from genetics, translational and disease pathway exploration, explore target engagement, decode mechanisms of action of drugs, and provide functional validation of novel drug targets.

• Be proactive and work collaboratively across disciplines, including molecular biologists, protein scientists, bioinformaticians, and software engineers

• Employ best reproducible research and data integrity practices to generate reusable analysis frameworks and reports to support Discovery Oncology target identification and validation efforts.

Education Minimum Requirement:

• Ph.D. in Bioinformatics, Biostatistics, Computational biology, Computer Science, Genetics, Immunology, Mathematics, Molecular Biology, Statistics or related field.

Required Experience and Skills:

• Passion to solve biological problems and identify problems that can be efficiently solved through computational methods and algorithms

• Experience with computational analysis and biological interpretation of diverse large-scale NGS experimental datasets

• Understanding the pros and cons of various algorithms for DNA-seq, RNA-seq, single-cell RNA-seq and/or functional genomics data

• Proven track record of applying machine learning algorithms and advanced computational methods to analyze single-cell RNA sequencing (scRNAseq) data, leading to the identification of novel patterns, cell populations, and functional insights

• Previous experience with experimental design of Oncology biological assays, statistical hypothesis testing, and biological interpretation

• Proficiency in at least one statistical programming language, such as R or Python

• Familiarity with public databases, and repositories of DNA, RNA and single cell profiling data, e.g. The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Clinical Proteomic Tumor Analysis Consortium (CPTAC), Dependency Map (DepMap).

• Skilled at integrating results generated from multiple omics data sources, and biological knowledge bases to customize analytical approaches for discovery research

• Interest in identifying novel applications of AI / machine learning strategies for biological target discovery

• Experience with AWS cloud computing infrastructure (e.g., S3, EFS, EC2, etc) and Linux environments.

• Experience with version control environments, such as Git

• Demonstrate the ability to learn, be proactive and motivated, and consistently focus on details and execution

• Excellent oral and written communication skills

Preferred Experience And Skills

• Strong background with a post-doctoral or relevant industry experience after completing graduate school

• Deep understanding of cancer biology and/or immunology, with knowledge of the latest research and trends in the field

• Expertise in utilizing network-based analysis frameworks to infer gene regulatory patterns and signaling pathways from next-generation sequencing (NGS) data, enabling the identification of potential therapeutic targets and conducting mechanism of action studies

• Applied experience and/or keen interest in employing transfer learning techniques to leverage knowledge gained from diverse NGS datasets, such as scRNAseq, bulk RNAseq, proteomics and spatial transcriptomics

• Strong publication record

Travel

• Up to 10% travel is required

Current Employees apply HERE (~~~)

Current Contingent Workers apply HERE (~~~)

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here (~~~) if you need an accommodation during the application or hiring process.

We are an Equal Opportunity Employer, committed to fostering an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status, or other applicable legally protected characteristics. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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We are proud to be a company that embraces the value of bringing diverse, talented, and committed people together. The fastest way to breakthrough innovation is when diverse ideas come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.

Learn more about your rights, including under California, Colorado and other US State Acts (~~~/)

U.S. Hybrid Work Model

Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as "remote".

The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate's relevant skills, experience, and education.

Expected US salary range

$151,900.00 - $239,200.00

Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listed here (~~~/) .

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully

Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

Yes

Travel Requirements:

10%

Flexible Work Arrangements:

Hybrid

Shift:

Not Indicated

Valid Driving License:

No

Hazardous Material(s):

n/a

Job Posting End Date:

12/16/2024

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.

Requisition ID: R322548