Über
Responsibilities
Lead statistical analyses and research data science solutions for small molecule and peptide workflows in early drug discovery. Develop and implement new machine learning workflows, including cutting-edge deep learning frameworks, to enable the discovery of new medicines. Explore and interpret the complex data outputs generated by high-throughput experimentation from across the organization. Apply rigorous computational methods to assist discovery scientists in generating novel, impactful hypotheses for target identification. Contribute directly to the design and optimization of property prediction models for small molecules. Collaborate closely with interdisciplinary, cross-organizational discovery teams to apply a variety of informatics and molecular modeling techniques. Provide stakeholders with an in-depth understanding of data sets and clear, concise interpretations of analytical results during experimental development. Conduct advanced research in machine learning applications, protein structure related models, or large-scale chemical foundation models for virtual screening. Education
Minimum Qualification: Bachelor's degree in Computational Physics, Computational Chemistry, Bioinformatics, Computer Science, or a relevant quantitative field. Accepted Advanced Degrees: Master's degree or PhD in Computational Physics, Computational Chemistry, Bioinformatics, Computer Science, or a relevant quantitative field is highly acceptable. Experience
Years of Experience: 0 to 3 years of experience (ideal for junior candidates, recent advanced degree graduates, or postdocs). Technical Skills: Highly skilled in Python for scientific computing (specifically utilizing libraries like NumPy and PyTorch) and hands-on data science/machine learning experience. Domain Knowledge: Working knowledge of biochemistry and/or general chemistry concepts. Infrastructure Familiarity: Experience working with high-performance computing (HPC) in a Unix/Linux OS environment, or familiarity with cloud computing environments (e.g., AWS). Preferred Experience (Nice to Have): Exposure to research projects within the pharmaceutical early discovery space, experience with chemical foundation models, or familiarity with protein structure modeling. Additional Information
Work Schedule: Hybrid role requiring 3 days onsite and allowing for 2 days of remote work per week. Work Location: Merck Facility in Rahway, NJ. Core Competencies: Requires an intellectually curious professional with excellent oral and written communication skills to effectively translate complex technical data results to multidisciplinary stakeholders.
Sprachkenntnisse
- English
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