Scientist I, Automation

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, no summarizing away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. We need to parse the job posting. Company Description: About AbbVie ... we can include as maybe "About the role"? Actually "About the role" is a heading for description of role. The company description could be part of "About the role" or maybe separate? The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to include only those with real content. Let's extract content: Job Description paragraphs: - "The Molecular Profiling and Drug Delivery (MPDD) function within the Small Molecule CMC organization is accountable for a broad range of deliverables across various stages of drug discovery and development. During lead optimization and through candidate selection, MPDD scientists utilize state of the art automation and computational tools supported by expertise in biopharmaceutics, drug delivery, and solid-state chemistry to collaboratively progress candidates with higher probability of success into development and advise clinical formulation strategy. From candidate selection through clinical proof of concept and product launch, MPDD scientists work in cross functional teams to identify the commercial solid form of the active pharmaceutical ingredient (API) and establish structure-property-performance correlations to help deliver robust commercial processes and align control strategies across drug substance and product. They also transition drug substance isolation processes and relevant physical characterization methods to commercial manufacturing sites and work within teams to ensure successful regulatory submissions. Drug Delivery scientists within AbbVie's MPDD organization work collaboratively with other functions within Development Sciences and Discovery to conduct developability assessment to select molecules with higher probability of success for clinical development and eventual commercialization. This includes profiling of physicochemical properties, development of preclinical formulations, identifying solutions to in vivo absorption challenges, and advancement of novel drug delivery strategies across multiple routes of administration that are aligned with program target product profiles and downstream partners. Modalities of interest include traditional small molecules as well as complex chemically synthesized modalities such as PROTACs and peptides. In this role, you will work in cross-functional teams in matrixed environments and engage in multidisciplinary problem solving." Second Job Description paragraph (duplicate heading): "AbbVies MPDD organization is seeking a highly motivated, creative, and collaborative scientist with expertise in assay development, chemical automation, and integrated workflow design for a Scientist I position. The primary role of this position will emphasize analytical chemistry, HPLC mass spectrometry (HPLCMS), laboratory automation, and implement automated and data-enabled workflows that accelerate decision-making and improve throughput in early development sciences. This individual will contribute to the profiling of physiochemical properties, screening and development of preclinical formulations, and the advancement of platform workflows for emerging modalities of interest. This role will work closely with cross-functional partners across discovery and development sciences to build and optimize integrated capabilities that support faster, data-driven, more efficient pipeline progression. The successful candidate will have strong hands-on experience in HPLCMS, assay development, automation, and the generation and interpretation of physicochemical data to inform developability. Experience with preclinical formulation strategies, workflow optimization, and enabling technologies for novel or complex modalities is highly desirable." Qualifications section: - "Scientist I typically requires Bachelors Degree or equivalent education with typically 5 years of experience, or Masters Degree or equivalent education with typically two years of experience in pharmaceutical or related industry. Preferred educational backgrounds include but are not restricted to Pharmaceutical Sciences, Pharmaceutical Engineering, Chemical/Biomedical Engineering, Chemistry and Materials Science. Familiarity and preferred hands-on experience in physicochemical property assessment related to understanding CMC developability profile and potential risk mitigation strategies. Experimental and automation techniques of interest include but are not limited to: plate-based optical spectroscopy, liquid handler operation, custom scientific programming and scripting, machine learning and model-building concepts, high-performance liquid chromatography (HPLC), mass spectrometry, powder X-ray diffraction (pXRD), optical microscopy, light scattering techniques, thermal analysis, and other biophysical characterization techniques. Experience with automated data capture, laboratory instrumentation integration, assay miniaturization, and data analysis workflows is desirable. Hands-on Experience with HPLCMS, high-resolution mass spectrometry, or related analytical platforms. Hands-on experience in assay development, automation, and workflow optimization, with an ability to design and implement efficient, reproducible, and scalable laboratory processes. Strong understanding of physiochemical property profiling and its application to early developability assessment, including methods relevant to solubility, stability, and other compound attributes that inform pipeline decisions. Familiarity with preclinical formulation development and screening strategies, including support for enabling formulations for emerging or complex modalities. Familiarity with analytical, biophysical, and in vitro techniques used to generate high-quality data for early development decision making. Experience collaborating with data scientists, computational chemists, or informatics partners. Excellent organizational skills, self-management, and attention to detail, with the ability to manage multiple priorities in a fast-paced environment." Key Competencies: list of bullet-like sentences. Additional Information: includes compensation range description, benefits, short-term incentive programs, note about pay, EEO etc. We need to extract Benefits and Pay if present. Benefits: "We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our short-term incentive programs." Pay: "Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future." But we don't see actual numbers. The posting didn't give a specific range; it just says compensation range described below but no numbers provided. Since we must not create Pay section unless posting actually states them (specific numbers). It says "The compensation range described below is the range..." but no actual numbers given. So we should not include Pay section because no specific numbers. Similarly Schedule: none. Benefits: we have specific benefits: paid time off, medical/dental/vision insurance, 401(k), short-term incentive programs. That's substantive. So include Benefits section. Now we need sections: About the role (maybe combine company description and role description?), Responsibilities, Requirements, Qualifications, Skills, Benefits. We need to decide what goes where. Typically: About the role: overview of role and team. Responsibilities: duties. Requirements: maybe education/experience. Qualifications: similar. Skills: competencies. But we must not duplicate. We need to preserve all substantive info; we can split logically. Let's map: - About the role: Could include company description (About AbbVie) and maybe high-level role description (MPDD function). But we must not repeat job title. We'll include a paragraph about AbbVie mission and MPDD function. - Responsibilities: The duties described in job description paragraphs: lead optimization, candidate selection, using automation, computational tools, progress candidates, advise clinical formulation strategy, identify commercial solid form, establish structure-property-performance correlations, transition drug substance isolation processes, ensure regulatory submissions, conduct developability assessment, profiling physicochemical properties, develop preclinical formulations, identify solutions to in vivo absorption challenges, advance novel drug delivery strategies, work in cross-functional teams, matrixed environments, multidisciplinary problem solving, emphasize analytical chemistry, HPLCMS, lab automation, implement automated workflows, contribute to profiling physiochemical properties, screening and development of preclinical formulations, advancement of platform workflows, build and optimize integrated capabilities, etc. We can combine into a bulleted list. - Requirements: Education/experience requirements: Bachelors + 5 years or Masters + 2 years in pharmaceutical or related industry. Preferred educational backgrounds list. - Qualifications: Could be the hands-on experience and technical skills list: HPLCMS, assay development, automation, workflow optimization, physicochemical property profiling, preclinical formulation strategies, analytical techniques, data capture, instrumentation integration, assay miniaturization, data analysis workflows, experience with data scientists, etc. But there is overlap with Requirements. Perhaps we treat Requirements as education/experience, Qualifications as technical skills and experience. - Skills: Key Competencies list (relationship building, fast learning, connecting ideas, raising bar, scientific curiosity, learning environment, embracing ideas, nurturing innovation). Also maybe "Excellent organizational skills, self-management, attention to detail, manage multiple priorities" could be skills. We need to avoid duplication but preserve all info. We'll try to allocate. Let's extract bullet points for responsibilities from paragraphs. Responsibilities bullet list: - Utilize state-of-the-art automation and computational tools supported by expertise in biopharmaceutics, drug delivery, and solid-state chemistry to progress candidates with higher probability of success into development and advise clinical formulation strategy (lead optimization through candidate selection). - Identify the commercial solid form of the active pharmaceutical ingredient (API) and establish structure-property-performance correlations to help deliver robust commercial processes and align control strategies across drug substance and product (candidate selection through clinical proof of concept and product launch). - Transition drug substance isolation processes and relevant physical characterization methods to commercial manufacturing sites. - Work within teams to ensure successful regulatory submissions. - Conduct developability assessment to select molecules with higher probability of success for clinical development and eventual commercialization. - Profile physicochemical properties. - Develop preclinical formulations. - Identify solutions to in vivo absorption challenges. - Advance novel drug delivery strategies across multiple routes of administration aligned with program target product profiles and downstream partners. - Work in cross-functional teams in matrixed environments and engage in multidisciplinary problem solving. - Emphasize analytical chemistry, HPLC mass spectrometry (HPLCMS), laboratory automation. - Implement automated and data-enabled workflows that accelerate decision-making and improve throughput in early development sciences. - Contribute to the profiling of physiochemical properties, screening and development of preclinical formulations, and advancement of platform workflows for emerging modalities of interest. - Build and optimize integrated capabilities that support faster, data-driven, more efficient pipeline progression. - Generate and interpret physicochemical data to inform developability. - Apply preclinical formulation strategies, workflow optimization, and enabling technologies for novel or complex modalities. That seems comprehensive. Requirements: Education/experience. - Bachelor's degree or equivalent with typically 5 years of experience, or Master's degree or equivalent with typically 2 years of experience in pharmaceutical or related industry. - Preferred educational backgrounds: Pharmaceutical Sciences, Pharmaceutical Engineering, Chemical/Biomedical Engineering, Chemistry, Materials Science. Qualifications: Technical/hands-on experience. - Hands-on experience with HPLCMS, high-resolution mass spectrometry, or related analytical platforms. - Hands-on experience in assay development, automation, and workflow optimization, with ability to design and implement efficient, reproducible, and scalable laboratory processes. - Strong understanding of physiochemical property profiling and its application to early developability assessment, including methods relevant to solubility, stability, and other compound attributes. - Familiarity with preclinical formulation development and screening strategies, including support for enabling formulations for emerging or complex modalities. - Familiarity with analytical, biophysical, and in vitro techniques used to generate high-quality data for early development decision making. - Experience with automated data capture, laboratory instrumentation integration, assay miniaturization, and data analysis workflows. - Experience collaborating with data scientists, computational chemists, or informatics partners. - Familiarity and preferred hands-on experience in physicochemical property assessment related to understanding CMC developability profile and potential risk mitigation strategies. - Experimental and automation techniques of interest include but not limited to: plate-based optical spectroscopy, liquid handler operation, custom scientific programming and scripting, machine learning and model-building concepts, HPLC, mass spectrometry, powder X-ray diffraction (pXRD), optical microscopy, light scattering techniques, thermal analysis, and other biophysical characterization techniques. Skills: Key Competencies and organizational skills. - Builds strong relationships with peers and cross-functional partners to enable higher