Zoetis, a global leader in animal health, seeks an enthusiastic colleague to join our Veterinary Medicine Research and Development (VMRD) PK/PD Team to discover and develop novel therapeutics for veterinary medicine. The successful candidate will be primarily responsible for designing, conducting, analyzing, and interpreting in vivo PK/PD studies in multiple species in support of projects from early research through late-stage development. This position will require a highly motivated and independent individual who can effectively collaborate with other team members to advance projects. POSITION RESPONSIBILITIES: - Design and analyze in vivo PK/PD, PK and TK studies in multiple veterinary species, including writing study protocols and reports. - Provide PK and PK/PD modeling and simulation to help select lead candidates and optimize dose regimens. - Collaborate with bioanalytical team to assess suitability of analytical assays and forecast analytical requirements for projects. - Lead development of scientific strategy across therapeutic areas with a focus on mechanistic platforms/biomarkers to aid in translation, measurement of target engagement, and dose regimen predictions. - Work collaboratively and communicate effectively with multidisciplinary teams to design and prosecute studies in line with the strategic direction of the project. - Present research results to scientific teams, management, and regulatory agencies. - Write sections of regulatory submissions, respond to inquiries from regulatory agencies, and maintain knowledge of regulatory guidance documents. REQUIRED EDUCATION AND EXPERIENCE: - Ph.D in pharmacology, pharmaceutical sciences, biochemistry, or related field. 2-4 years of post-doctoral experience in pharmaceutical development is highly desirable. DVM DACVCP or DVM Dipl. ECVPT is highly desirable. - Proven ability to design, analyze and interpret in vivo PK and PK/PD studies. Experience with biotherapeutics (protein therapeutics) is highly desirable. - Skilled in the use of PK and PK/PD analysis software such as WinNonlin, Monolix or Watson. - Must have excellent verbal & written communication skills. - Self-starter, able to prioritize work and work efficiently with minimal supervision. - Working knowledge of bioanalytical methodology. - Experience in PK/PD modeling and simulation such as PBPK, QSP or population PK modeling using NONMEM, R, or related software is highly desirable. The US base salary range for this full-time position is $114,000- $185,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the base pay target range for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. This position is also eligible for short-term incentive compensation This position is also eligible for long-term incentives In addition to compensation, Zoetis offers a comprehensive benefits package that supports the physical, emotional and financial wellbeing of our colleagues and their families including healthcare and insurance benefits beginning on day one, a 401K plan with a match and profit-sharing contribution from Zoetis, and 4 weeks of vacation. Visit zoetisbenefits.com to learn more. Full time Regular Colleague Any unsolicited resumes sent to Zoetis from a third party, such as an Agency recruiter, including unsolicited resumes sent to a Zoetis mailing address, fax machine or email address, directly to Zoetis employees, or to Zoetis resume database will be considered Zoetis property. Zoetis will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume. Zoetis will consider any candidate for whom an Agency has submitted an unsolicited resume to have been referred by the Agency free of any charges or fees. This includes any Agency that is an approved/engaged vendor but does not have the appropriate approvals to be engaged on a search. Notice: Zoetis Recruiters will contact candidates via email from an address ending in @zoetis.com and may also initially connect with candidates through LinkedIn, including LinkedIn InMail. Zoetis does not use Gmail, Outlook, Yahoo, or other web-based/generic email domains to communicate about job opportunities, interviews, or offers of employment. If you receive a recruitment-related email message claiming to be from Zoetis that does not come from @zoetis.com, please treat it as suspicious. For your security, do not reply, click links, open attachments, share personal or financial information, or send money in response to unexpected or questionable recruitment communications. Zoetis 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 or any other protected classification. Disabled individuals are given an equal opportunity to use our online application system. We offer reasonable accommodations as an alternative if requested by an individual with a disability. Please contact Zoetis Colleague Services at zoetiscolleagueservices@zoetis.com to request an accommodation. Zoetis also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must possess or obtain authorization to work in the US for Zoetis. Zoetis retains sole and exclusive discretion to pursue sponsorship for the acquisition or maintenance of nonimmigrant status and employment eligibility, considering factors such as availability of qualified US workers. Individuals requiring sponsorship must disclose this fact. Please note that Zoetis seeks information related to job applications from candidates for jobs in the U.S. solely via the following: (1) our company website at www.Zoetis.com/careers site, or (2) via email to/from addresses using only the Zoetis domain of “@zoetis.com”. In addition, Zoetis does not use Google Hangout for any recruitment related activities. Any solicitation or request for information related to job applications with Zoetis via any other means and/or utilizing email addresses with any other domain should be disregarded. In addition, Zoetis will never ask candidates to make any type of personal financial investment related to gaining employment with Zoetis.

Title: Scientist I - Scientist II, Computational Protein Generation Location: Somerville, MA Job Description: The Role: We are seeking a creative, motivated Computational Scientist to join our Model-Driven Design team at Generate:Biomedicines. You will join a talented and collaborative group of ML scientists, engineers, and wet-lab scientists dedicated to redefining how medicines are made. This role sits at the intersection of machine learning, structural biology, and therapeutic development, where you will stay at the leading edge of internal and external models for de novo protein design and systematically benchmark, integrate, and apply them within tightly integrated design–build–test–learn cycles to advance our therapeutic pipeline and impact patients' lives. The ideal candidate combines deep structural intuition with a demonstrated ability to rapidly assess and apply protein design methods and metrics across diverse design problems, thinks in terms of reusable capabilities, benchmarks, and feedback loops across applications, and uses modern generative models and experimental readouts to guide iterative design cycles across modalities. You don't just run existing tools; you understand what's missing from current approaches and are driven to fill those gaps. This role is based in our Somerville, MA office with flexibility for hybrid work. Here's how you will contribute: - Model application and optimization: develop, validate, and productionize de novo protein generation protocols and optimization techniques on our experimental platform, using measured data in-the-loop to iteratively refine models across modalities and therapeutic applications. - Define and implement in silico metrics: design, interpret, and implement biophysical and functional metrics for evaluating generated designs, leveraging existing literature, adapting known metrics to new contexts, and performing original research to benchmark and deploy new scoring approaches. - Benchmark foundation models and guide their application: rigorously evaluate new models and tools and provide quantitative conclusions on where they are best applied to generate new therapeutics, including designing systematic internal benchmarks and discovering how to expand model capabilities to prosecute new therapeutic targets in novel ways and to maximize reuse across targets and programs. - Propose new therapeutic strategies: identify and implement solutions to create new therapeutics through mechanisms of action unlocked by de novo tools and modalities. - Partner cross-functionally to drive therapeutic development: work closely with experimental colleagues, biologists, and clinical scientists to define design objectives, interpret experimental readouts, and guide iterative design-build-test-learn cycles that advance programs. - Advance the state of the art: push forward sequence–structure–function understanding with a focus on reusable platform capabilities and model-informed feedback loops. - Integrate agentic tools into workflows: leverage agentic AI tools to rapidly iterate on models, benchmarks, scores, critics, and other analysis tools, accelerating the pace of discovery. - Build production-quality tools: develop robust, production-ready code in a collaborative team setting and present scientific progress in regular research meetings. What Success Looks Like - First 3 months: You have familiarized yourself with the proprietary Generate platform and either completed a first-pass design for a therapeutic program or built and applied your first internal tool or benchmark. - By 6 months: You are fully fluent in the Generate stack. You have taken ownership of building or extending a segment of the platform applied to protein design, including designing or maintaining key benchmarks or metrics, or you are contributing materially to an active therapeutic program, driving design decisions with increasing independence. - By 12 months: Given strategic direction, you operate with full autonomy scoping, building, and deploying new tools and methods that advance our protein design capabilities and therapeutic pipeline and strengthen our continuously learning, model-informed design platform. The Ideal Candidate will have: - PhD in Computational Biology, Biophysics, Computer Science, or a related field, with demonstrated experience in protein design applications. - 0–2 years of experience applying computational and/or ML methods to protein design, modeling, or prediction. - Hands-on experience with machine learning and generative modeling for protein design, including familiarity with modern methods such as RFDiffusion, ProteinMPNN, BindCraft, BoltzDesign, or equivalent approaches and how to deploy or evaluate them in practice. - Strong structural intuition and understanding of protein biophysics with the ability to quickly assess and adapt design methods and metrics to new problems. - Familiarity with protein therapeutic modalities such as antibodies, mini-proteins, VHHs, peptides, or enzymes, and an eagerness to deepen expertise across these within de novo design workflows. - Proficiency in Python and scientific computing; comfort working in a production codebase. - Experience designing, running, or interpreting benchmarks for computational or generative methods and drawing quantitative conclusions about model applicability and limitations. Strongly Preferred - Experience designing, executing, and interpreting experiments and experimental data (e.g., binding assays, stability measurements, structural characterization) and using those readouts to inform computational design iterations. - Familiarity with agentic AI tools and their integration into scientific workflows. - Exposure to structure-based design techniques and computational tools for modeling protein-protein interactions. - Track record of translating research ideas into working software or reusable platform components used across multiple projects or applications. About Generate Biomedicines We are a clinical-stage generative biology company pioneering the AI revolution in drug design and development. We are advancing a new approach to drug creation—one grounded in the ability to design proteins with defined biological intent. By integrating machine learning with large-scale experimentation, this approach aims to reduce the uncertainty, time, and cost associated with developing protein-based medicines. Founded in 2018, we are advancing a growing pipeline of clinical and preclinical programs across multiple disease areas and protein modalities. By unifying computational design and clinical development within a single operating model, we translate this approach into clinical-stage programs and are leading a shift from traditional drug discovery toward systematic drug generation. At Generate:Biomedicines, we collaborate across disciplines in new ways to invent and innovate. We bring diverse perspectives to a shared goal of delivering better medicines to patients in need, faster, guided by our values and leadership behaviors. Generate:Biomedicines is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Recruitment & Staffing Agencies: Generate:Biomedicines does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Generate:Biomedicines or its employees is strictly prohibited unless contacted directly by the Company’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Generate:Biomedicines and the Company will not owe any referral or other fees with respect thereto. Compensation: The base salary range provided reflects our current estimate of what we anticipate paying for this position. Your actual base salary will be based on several factors, including job-related skills, experience, internal equity, relevant education or training, and market dynamics. In addition, you will be eligible for an annual bonus, equity compensation, and a competitive benefits package. Per Year Salary Range $140,000 - $200,000 USD

Support lab operations by maintaining resources, managing mouse colonies, and conducting behavioral experiments. Collaborate with researchers and oversee the core facility's reservations, ensuring efficient use and upkeep of laboratory supplies.

• Develop a novel research study identifying actionable drivers of youth mental health • Produce publication-quality research suitable for submission to a peer-reviewed journal • Generate funder-ready and policy-relevant outputs that inform real-world decision-making • Translate complex data into clear insights for policymakers, healthcare systems, and community organizations • Contribute to Surgo Health’s growing portfolio of intervention-oriented research and thought leadership • Design and execute a research project using the Youth Mental Health Tracker dataset and, where relevant, external datasets (e.g., NSDUH, ACS, policy datasets) • Identify novel mechanisms, risk levers, or protective factors that can inform intervention • Articulate clear intervention pathways and decision-making use cases • Develop outputs tailored to multiple audiences, including academic, policy, and funder stakeholders • Collaborate with Surgo’s research scientists for methodological guidance and translational framing