Role Summary
Pfizer’s Machine Learning Hub is seeking a passionate, creative, and experienced machine learning researcher to design and implement new machine learning tools to accelerate drug discovery. As a member of our Machine Learning Research team, you will design new approaches to derive insights from Pfizer’s proprietary data and external datasets to generate testable hypotheses across the drug discovery continuum with a focus on extracting biological knowledge. The individual will also design, establish, and manage internal and external collaborations to advance Pfizer’s ML capabilities. The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery. Our team is located in Cambridge, MA, USA and Berlin, Germany and this role can accommodate an exceptional candidate in either location.
Role Responsibilities
Principal downstream application domains include indication expansion, target identification, disease mechanism elucidation, and partnering with practitioners in these areas to advance the state-of-the-art.
Development and implementation of advanced machine learning models specifically designed for analyzing heterogeneous biological data. This includes data from genomics, proteomics, metabolomics, and other biological sources.
Advance the internal machine learning tech stack to cope with spurious correlation, obscuring variation and inherent multimodality of biomedical, chemical, and ‘omics data
Research, design and implement learning algorithms for analysis problems related to drug discovery
Be an active member of a highly interdisciplinary team
Conceive, execute and evaluate studies and experiments, interpret the results and present them to scientist in other functions
Strengthen external visibility and scientific excellence through publishing / presenting work in reputed journals and conference/workshop venues and engaging with the scientific community
Minimum Qualifications
Formal training in Biology, Computational Biology, Statistics, Machine Learning, or a related technical discipline
PhD and 2+ years of relevant research experience in developing machine/deep learning-based solutions and a sincere interest for computational life sciences
Hands-on experience in handling, processing, integrating, and analyzing large heterogenous biological data sets related to industrial drug discovery research (e.g., sc/snRNAseq, ATAC-seq, genomics, proteomics, etc.)
Proven expertise in developing machine learning for computational biology
Highly creative person with outstanding problem-solving skills to tackle complex analysis tasks in a timely fashion
Strong publication record and demonstrated contributions to the field
Solid expertise with ML libraries such as PyTorch, Lightning is mandatory! Programming skills in Python must be top-notch. Experience with relevant libraries of the Python scientific stack is a big plus.
Familiarity with GPU computing both on-premises and on cloud platforms
Fluency with common version control tools and collaborative coding
Passion and curiosity for data and proven ability to take ideas from prototype to production
Strong interpersonal skills, distinct collaborative attitude, excellent written and verbal communication
PHYSICAL/MENTAL REQUIREMENTS
Ability to perform mathematical calculations and ability to perform complex data analysis. Relocation support available.
Relocation assistance may be available based on business needs and/or eligibility.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
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