Associate Scientist (Tissue-based Imaging Biomarkers), Biomarkers & Data Analytics, Quantitative Biosciences

Job Description

At our company, we are committed to becoming the premier, research-intensive biopharmaceutical company and are dedicated to providing leading innovations and solutions for today and the future.

Our Research Scientists are our Inventors. We identify and target steps in disease mechanisms or pathways that could be inhibited or enhanced. Our goal is to isolate a compound that is effective against a disease target. Using innovative thinking, state-of-the-art facilities and robust scientific methodology we collaborate to discover the next medical breakthrough.
 

Join our Biomarkers & Data Analytics team at our research laboratory in Singapore. We integrate biology, technology, and data science to discover novel biomarkers in disease biology to accelerate drug discovery and development. In this role, you will be responsible in operationalizing our studies in AI digital pathology and spatial biology for various disease areas, with the objective to discover novel biomarkers. Additionally, you will collaborate closely with colleagues from various cross-functional teams (including biologists, pathologists, and AI/ML experts), as well as external vendors and collaborators to carry out these studies.
 

WHAT YOU WILL DO

Responsibilities include, but are not limited to: 

• Execute imaging biomarker study operations and coordination with internal stakeholders and external vendors/collaborators to meet demanding discovery program timeline.
• Perform routine image analysis using established in-house analysis pipeline for digital pathology/spatial biology and prepare visualization and study reports.
• Proactively identify areas of improvement in existing AI tool/analytics workflows to drive innovation and enhance operational efficiency.
• Conduct relevant literature studies to formulate methods and hypothesis using the application of AI digital pathology/spatial biology in understanding disease biology.
• Contribute to authoring documentation related to image analysis workflow/pipeline and SOP.
• Responsible for managing tissue sample shipment, sample tracking and monitoring study progress for AI digital pathology/spatial biology studies.
• Support the team in developing workflow for digital pathology/spatial biology, including assisting with lab-related work (e.g. histology, protocol optimization, whole slide imaging, microdissection).
• Collaborate with cross-functional teams such as biologists, pathologists, and AI/ML experts on projects.
• Participate in team meetings and contribute to discussions on project progress and findings. Attend and potentially present at relevant conferences, demonstrating a commitment to professional growth and knowledge expansion.
• Present findings and insights to the team and stakeholder.
   

WHAT YOU MUST HAVE

To be successful in this role, you will have:

• Bachelor’s or Master’s degree in engineering, Computational Sciences or Biomedical/Life Sciences disciplines with research exposure in medical image analysis, preferably pathological, histological or tissue imaging.
• Hands-on experience with image analysis and processing, and data analysis and visualization using Python (seaborn, matplotlib) or R (ggplot2, corrplot).
• Understanding of spatial biology/omics imaging; hands-on experience with the data analytics component is plus.
• Hands-on experience with deep learning and/or machine learning tools such as scikit-learn, pytorch, and tensorflow.
• Understanding of biostatistics.
• Hands-on experience in handling tissue/histological slides and any histology-related wet lab work is a plus.
• Collaborative mindset and excellent communication skills to successfully partner and work with other team members as well as stakeholders across groups to achieve results.
• Independent and proactive approach in managing projects, prioritization, and planning to complete work efficiently and timely.
• Innovative mindset for experimenting with new ideas and approaches.

WHAT YOU CAN EXPECT

• Integration of biology, imaging, and data science to solve complex challenges related to drug development
• Exposure of AI/ML in digital pathology/spatial biology
• Collaboration with a team committed to leveraging AI/ML for drug development.
• Opportunities to present science to stakeholders and collaborators.
• A supportive working environment that fosters career growth and continuous learning.

 

Additional Information:

• Please provide a LinkedIn profile, publications in conferences/journals, or any relevant profiles (Google Scholar, Github, Stack Overflow, Arxiv, and/or Kaggle) if available.

Current Employees apply HERE

Current Contingent Workers apply HERE

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:

Temporary (Fixed Term)

Relocation:

VISA Sponsorship:

Travel Requirements:

Flexible Work Arrangements:

Not Applicable

Shift:

Valid Driving License:

Hazardous Material(s):

Required Skills:

Biology, Biomarkers, Bioscience, Data Analytics, Data Modeling, Data Visualization, Digital Pathology, Drug Development, Histology, Image Analysis, Imaging Biomarkers, Life Science, Machine Learning, Science, Software Development, Teamwork

Preferred Skills:

Job Posting End Date:

10/30/2024

*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.