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SalaryJob Description
Our Artificial Intelligence Machine Learning (AI/ML) capabilities are critical accelerators to our mission to delivering towards inventing new medicines that save and improve lives. Core to the Data, AI and Genome Sciences (DAGS) function is an AI/ML-first approach to improving target and biomarker discovery, validation and selection and elucidating complex disease mechanisms. As Director of Data Science, Foundation Model Lead you will build state-of-the art AI/ML capabilities for analyzing genomic, multi-omic, imaging, single cell, and deep phenotypic and clinical data/model systems to derive clinically relevant insights for disease biology and target discovery. You will be part of a cross-functional team of computational biologists, bioinformaticians, data scientists, software engineers, and machine learning engineers that strive to identify therapeutic targets. You will report to the Executive Director, Head of AI/ML
Primary Responsibilities:
Lead technically the development and implementation of pre-trained transformer-based foundation and cutting-edge machine learning models for target discovery, leveraging large-scale biological and imaging data.
Collaborate closely with cross-functional teams, including data scientists, biologists, and software engineers to develop and deliver scalable machine learning solutions.
Integrate diverse datasets, including genomics, transcriptomics, and proteomics to extract clinically relevant insight and uncover disease biology and novel drug targets.
Know the latest research and identify opportunities to leverage new advancements in ML for target and biomarker discovery.
Contribute to publications and present results at internal and external scientific conferences and workshops.
Required Experience and Skills:
PhD in machine learning, computer science, physics, or related field and 8+ years’ experience with data science, developing and prototyping large-scale machine learning models, such as deep learning, CNN, GNN, and transformer-based Foundation Models OR MS and 10+ years of experience OR BS and 14+ years of experience.
Demonstrated hands-on experience in developing, training, and transfer learning of large-scale transformer-based Foundation Models.
Good understanding of the underlying algorithmic approaches of traditional and modern machine learning approaches.
Strong programming skills, particularly in languages such as Python, and proficiency in relevant machine learning libraries (PyTorch)
Interest in life sciences problems and disease biology, and willing to learn from and teach others.
Excellent communication skills, self-motivation, and ability to work collaboratively in multi-disciplinary team.
Preferred experience:
Relevant publications in scientific journals and experience contributing to research communities, including NeurIPS, ICML, ICLR, etc preferred.
This is a hybrid position, with an expectation of 3 days/week onsite.
NOTICEFORINTERNALAPPLICANTS
In accordance with Managers' Policy - Job Posting and Employee Placement, all employees subject to this policy are required to have a minimum of twelve (12) months of service in current position prior to applying for open positions.
If you have been offered a separation benefits package, but have not yet reached your separation date and are offered a position within the salary and geographical parameters as set forth in the Summary Plan Description (SPD) of your separation package, then you are no longer eligible for your separation benefits package. To discuss in more detail, please contact your HRBP or Talent Acquisition Advisor.
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Employees working in roles that the Company determines require routine collaboration with external stakeholders, such as customer-facing commercial, or research-based roles, will be expected to comply not only with Company policy but also with policies established by such external stakeholders (for example, a requirement to be vaccinated against COVID-19 in order to access a facility or meet with stakeholders). Please understand that, as permitted by applicable law, if you have not been vaccinated against COVID-19 and an essential function of your job is to call on external stakeholders who require vaccination to enter their premises or engage in face-to-face meetings, then your employment may pose an undue burden to business operations, in which case you may not be offered employment, or your employment could be terminated. Please also note that, where permitted by applicable law, the Company reserves the right to require COVID-19 vaccinations for positions, such as in Global Employee Health, where the Company determines in its discretion that the nature of the role presents an increased risk of disease transmission.
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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, generally Tuesday, Wednesday and either Monday or 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”.
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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:
RegularRelocation:
DomesticVISA Sponsorship:
YesTravel Requirements:
No Travel RequiredFlexible Work Arrangements:
HybridShift:
1st - DayValid Driving License:
NoHazardous Material(s):
n/a
Required Skills:
Preferred Skills:
Requisition ID:R278537
