Your primary responsibilities will include providing leadership to define and coordinate the data strategy that enables data-driven, model-based analytics for improved gene-edited germplasm, including accelerating data connectivity across the editing pipeline with multi-functional teams. You will also lead cross-functional projects with partners across Crop Science to automate decision making and connect data assets that accelerate development of gene-edited products.

In addition, you will translate complex business data knowledge, scientific workflows, and product needs into clear technical implementation plans that can be executed by data scientists, data engineers, and developers. You will design and guide the development of robust data systems and analytics pipelines that support a wide variety of genomic and computational biology use cases and can scale with future business needs.

As a key communicator and integrator between scientific, technical, and business stakeholders, you will align roadmaps, prioritize initiatives, and ensure that data and analytics solutions deliver measurable value. You will also attract, mentor, and develop talent, serving as a coach for peers and colleagues in key areas of expertise to support their professional growth and build a strong data and analytics community.

Finally, you will champion and support Health, Safety & Environment, Compliance, Business Conduct, and Human Rights policies and culture in all activities and collaborations.

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In this role, you will drive an impactful gene editing program by identifying gene editing targets and alleles that result in desired phenotypic impact, working with a diverse set of data inputs to develop genotype-to-phenotype predictions using some of the industry's most extensive and global agriculture and genetic datasets.

As a member of the Biology and Genome Design community, you will actively build your own acumen and capabilities while modeling best practices for others and partnering closely with cross-functional scientific, engineering, and IT teams across the company.

Responsibilities

• Produce and document recommendations for alleles that deliver desired phenotypic impact, contributing to innovative gene editing strategies
• Develop and apply state-of-the-art genetic discovery tools to identify novel genetics with predicted optimal phenotypic performance by leveraging diverse genomic and phenotypic datasets
• Develop robust workflows and analysis pipelines that enable cross-team communication, data sharing, and decision-making, supporting iterative learning from key experiments to shape research direction
• Identify and refine methods for capturing complex genetic interactions and the influence of genetic variation on observed phenotypes to improve design and prediction for current and future gene editing pipelines
• Lead or assist in the gathering, curation, quality control, and analysis of new data sources (e.g., functional genomics, phenomics) across Research and Development (R&D) teams
• Collaborate closely with cross-functional and cross-cultural scientific, engineering, and IT partners to align gene editing and data science approaches with pipeline and business needs
• Influence key stakeholders by clearly communicating data-driven insights, challenges, and opportunities to facilitate solutions to complex scientific and technical problems

Requirements

• PhD in Biological Sciences, Computational Biology, or a related field
• At least 3 years of post-PhD experience working in gene editing, functional genomics, or closely related fields
• Demonstrated ability to collect, analyze, and leverage complex biological datasets and translate them into testable hypotheses
• Experience with advanced computational and analytical tools in molecular biology, genetics, and biochemistry
• Distinct communication skills with fluency in English, both written and verbal

Preferred Qualifications

• Educational preparation or applied experience in at least one of the following areas: Plant Biology, Genetics, Molecular Biology, Machine/Deep Learning, or other closely related discipline
• Demonstrated experience working collaboratively in cross-functional and cross-cultural teams to achieve common goals
• Ability to influence key stakeholders by articulating challenges and opportunities to drive solutions to complex scientific and organizational challenges
• Results-oriented mindset with demonstrated ability to prioritize and advance multiple projects at the enterprise level

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Your primary responsibilities will be to:

• Guide the development of highly connected data systems that enable data-driven, model-based analytics to improve pipeline effectiveness and efficiency;
• Work with multifunctional teams to enable data connectivity across the editing pipeline, integrating information from lab, greenhouse, and field operations;
• Collaborate with partner teams across Crop Science (Gene Editing, IT Enterprise, Data and Engineering) to automate decision making and improve operational efficiency to accelerate development of gene-edited products;
• Serve as a key communicator translating business data knowledge and operational workflows into clear technical implementation plans for data scientists, data engineers, and developers;
• Demonstrate autonomy in building relationships and networks within your unit and across functions, most often with members of the Crop Genome Editing team and closely aligned partner teams;
• Act as a consultant to leadership and colleagues on digital strategy and data-driven operations through clear, organized, and influential communication;
• Actively build your own acumen in biology, genome design, and digital operations while sharing best practices and learnings with the broader Biology and Genome Design community.

We seek an incumbent who possesses the following qualifications:

• PhD in Computational Biology, Computer Science and Engineering, or another relevant scientific field with a minimum of 6 years of relevant experience, or MS with 10+ years of relevant experience;
• Demonstrated track record developing data systems and pipelines that enable efficient product delivery and operational modeling;
• Demonstrated experience working collaboratively in cross-functional and cross-cultural teams to achieve common goals;
• Demonstrated experience leading and influencing activities of cross-functional teams without direct reporting relationships;
• Ability to lead and influence key stakeholders through challenges and opportunities and to facilitate solutions.

Preferred qualifications include experience building data pipelines as a ML DevOps Engineer or Data Engineer, experience with Operations Research, and experience analyzing large biological datasets and developing analytical pipelines using Python, R, or similar software and languages.

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In this role, you will lead cross-functional projects with IT, Data Engineering, Genome Editing, and other partner teams to automate decision making and connect data to accelerate development of gene-edited products. You will translate complex biological processes into scalable digital workflows that support decision making, advancement, and prioritization within the gene editing program. Your strong ability to collaborate and lead in cross-functional, multi-disciplinary teams will be crucial in influencing without authority and aligning diverse stakeholders around shared digital solutions.

As a member of the Biology and Genome Design community, you will actively build your own acumen and capabilities while sharing best practices with others. You will serve as a key communicator and thought partner on digital enablement strategy, clearly articulating requirements, trade-offs, and opportunities to scientific and non-scientific stakeholders.

We seek an incumbent who possesses a PhD in Genomics, Computational Biology, Evolution, Quantitative Genetics, or another relevant scientific field with a minimum of 6 years of relevant experience, or an MS with 10+ years of experience developing data systems and analytics pipelines that enable product delivery using genetic and computational biology datasets.

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The design space of biomolecules is unimaginably vast , far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions.

We advance the state of the art in molecular design by training large-scale foundation models and developing cutting-edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding.

You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs.

Responsibilities

• Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise

• Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design

• Analyze, visualize, and communicate results to support team efforts in improving models and data

• Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production

• Work with biologists to collect data for the training and evaluation of generative models of biomolecules

• Provide mentorship and technical direction to team members as appropriate

Qualifications

• 3+ years of hands-on experience developing ML models

• Demonstrated track record of implementing, training, improving advanced machine learning models

• Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework

• Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET

• Readiness to travel several times a year for company retreats and business events

Compensation

$200K – $275K + Bonus + Equity

Benefits

• A competitive compensation package

• 30 days paid vacation per year

• Comprehensive health insurance for US based employees

• 401K with company match for US based employees and Direktversicherung for German employees

• Quarterly company-wide retreats

• Monthly wellness benefit

• Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland

• Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning & Development platform EdX and Hone

• A buddy to help you get settled

At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.

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Key responsibilities include:

• Design and execute capability evaluations to assess the capabilities of new models
• Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers
• Analyze safety system performance in traffic, identifying gaps and proposing improvements
• Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces
• Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle
• Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety
• Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these

You may be a good fit for this role if you have a PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, or equivalent professional experience. You should also have extensive experience in scientific computing and data analysis, with proficiency in programming (Python preferred), deep expertise in modern biology, including both 'reading' and 'writing' techniques in biology, familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks, strong analytical and writing skills, and a passion for learning new skills and adapting to changing techniques and technologies.

Preferred qualifications include background in AI/ML systems, particularly experience with large language models, experience in developing ML for biological systems, and extensive experience in complex projects with multiple stakeholders.

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Rezo Therapeutics is a biopharma company that aims to increase the success rate of drug development by building a disease-agnostic, fully-integrated, network biology platform.

We are leveraging a unique integrated approach, combining capabilities in genetics, proteomics, structural biology and AI to generate deep biological insights and novel therapeutic approaches.

Located in San Francisco's vibrant Mission Bay neighborhood, Rezo is in close proximity to UCSF, numerous urban amenities, and outdoor recreational opportunities.

Responsibilities

If you do not see a job listing that matches your specific background, please apply to this posting as we will be looking for exceptional individuals in the following areas:

Proteomics

• Develop industry scale assays using in-house mass spectrometers
• Execute platform projects centered on PPI mapping, proximity labeling, post-translational modification and abundance proteomics
• Support drug discovery campaigns and develop target-based screens

Genetics

• Develop multimodal single and combinatorial genetic screens using CRISPR technologies
• Collaborate with target discovery teams to provide genetic support for targets and drug MOA

Chemical Biology and Protein Sciences

• Develop HTS small molecule screening campaigns and create robust target assays for drug development
• Drive enzymology, biophysics and protein binding analysis efforts
• Help build out the structural biology platform (including crystallography & Cryo-EM)
• Develop chemical biology tools to map ligandable pockets and aid in drug development

Cancer Biology

• Implement cutting edge molecular and cellular techniques to determine target functions in cell-based solid tumor models
• Develop data packages to prioritize targets and nominate candidates to the drug discovery stage
• Individuals with expertise in oncogene/tumor suppressor pathways and/or drug resistance are especially encouraged to apply

Computational Biology, Data Science

• Develop novel algorithms and apply deep learning-based approaches to network and proteomics datasets
• Implement cloud infrastructure, pipelines, and UI/UX for data analytics
• Conduct bioinformatic and statistical analyses of large, multimodal datasets

Benefits

• Medical (HMO or PPO), dental, and vision insurance
• Discretionary time off policy
• Company holidays (including summer and winter shutdown)
• 401(k) retirement savings program
• Commuter / Mass Transit Benefit Program
• Healthcare Flexible Spending Account (FSA)
• Dependent care Flexible Spending Account (FSA)
• Parental leave
• Competitive compensation
• Flexible work schedule

Equal Employment Opportunity

At Rezo we value a diverse, equitable, inclusive workplace and provide equal employment opportunity to all persons without regard to race, color, sex, gender identity, gender expression, religion, age, national origin, ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.

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You will be responsible for getting our state-of-the-art lab processes to interface with the rest of our systems. Depending on your skills and our needs, you'll be working on projects including distributed systems, system integration, database operations, and ETL.

As a member of a fast-growing team, you’ll take the lead on major projects and collaborate actively with our world-class team of engineers, scientists, designers, and product managers.

You are passionate about building reliable, maintainable, scalable, and fault-tolerant backend services, and you will have a significant impact on the continued growth of a high-profile technology organization that is changing the landscape on early cancer detection.

The role reports to our engineering management team. This role will be a Remote role.

Responsibilities:

• Design, develop, and deploy reliable, maintainable, scalable, and fault-tolerant LIS/LIMS software and backend services that power both our internal systems.
• Collaborate with team members for code and design reviews.
• Work with scientists, product analysts, technical product managers, and other engineers to solve complex problems in the face of lots of dynamism and uncertainty.
• Provide on-call support on a rotational basis.
• Guide and champion engineering hygiene and culture as a core part of the engineering backbone.

Requirements:

• BS in Computer Science, Engineering or related field, or equivalent training, fellowship, and/or work experience.
• 3+ years of experience as a part of a software development team successfully shipping a software product.
• Expertise with Java.
• Experience with LIS/LIMS development, configuration, and deployments.
• Experience designing and implementing scalable backend systems.
• Excellent written and verbal communication skills.
• The ability to thrive in an environment where collaboration, communication, and compromise are an expected part of your day-to-day work.
• A mindful, transparent, and humane approach to your work and your interactions with others.

Nice to have:

• Experience with Python.
• Experience in Kubernetes, Docker, MySQL, Microsoft Azure or Google Cloud Platform.
• Domain-specific experience in computational biology, genomics or a related field.

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The role reports to the Director of Computational Biology. This role can be Hybrid (2-3 days onsite in Brisbane, CA) or Remote role.

Responsibilities:

• Plan and execute development experiments for our multiomics cancer screening tests.
• Partner cross-functionally with computational, development, regulatory, and quality leaders to develop and execute a regulated development strategy working toward FDA approval.
• Use your quantitative skills to develop computational methods and interpret complex experimental results in order to optimize and validate innovative technology for sample collection, preparation, and detection.
• Develop and execute appropriate experimental design and analysis plans for Development, Verification, and Validation studies, closely partnering with Biostatistics, Development, and Pre-Analytics teams.
• Work closely with molecular and computational research teams developing our IVD products for blood-based molecular assays involving cell-free DNA.
• Impact patient lives through the development and launch of high-quality cancer screening technologies.

Requirements:

• Post-graduate degree (MS or PhD) in statistics, computational biology, bioinformatics, cancer biology, or related quantitative field.
• 3+ years of industry experience.
• Experience with molecular biology and next-generation sequencing.
• Experience in experimental design and analysis of high-throughput, quantitative technologies.
• Familiarity with and ability to select and leverage bioinformatics tools for the above molecular assays.
• Experience in applied statistics, such as in hypothesis testing, GLM, and appropriate use of simulation.
• Expertise in data analysis and visualization using R (tidyverse), or Python statistical packages (Numpy, Matplotlib, Pandas), or equivalent, under version control.
• Excellent oral and written communication skills to communicate to scientific and broader audiences, with keen attention to detail.
• Ability to work on a cross-functional team in our highly collaborative environment, working with both computational and experimental scientists.

Nice to Have:

• Experience in the development of diagnostic devices in a regulated environment (PMA, 510(k), CE-IVD) preferred.
• Experience with a variety of NGS methods (e.g., WGS, target capture with UMI, bisulfite sequencing, RNA-seq).

Benefits and Additional Information:

The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education.

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They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organisation dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

Responsibilities:

• Independently pursue cutting-edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.)
• Build new models or fine-tune existing models to identify biological changes resulting from disease
• Build models that achieve high accuracy and that generalise robustly to new data
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms
• Work closely with ML Engineering partners to ensure that Freenome's computational infrastructure supports optimal model training and iteration
• Take a mindful, transparent, and humane approach to your work

Requirements:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics
• 6+ years of post-doc or post-PhD industry experience achieving impactful results using relevant modelling techniques
• Expertise demonstrated by research publications or industry achievements, in driving independent research in applied machine learning, deep learning and complex data modelling
• Practical and theoretical understanding of fundamental ML models like generalised linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation
• Practical and theoretical understanding of DL models like large language models or other foundation models
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; PyTorch, TensorFlow and JAX; and ML platforms like Hugging Face
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations
• Proficient at productive cross-functional scientific communication and collaboration with software engineers and computational biologists
• A passion for innovation and demonstrated initiative in tackling new areas of research

Nice to have:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models
• Experience in NGS data analysis and bioinformatic pipelines
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems

Benefits and additional information:

• The US target range of our base salary for new hires is $199,675.00 - $283,500.00. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company's sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education.
• Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
• Applicants have rights under Federal Employment Laws.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

We are looking for biological scientists to help build safety and oversight mechanisms for our AI systems. As a Safeguards Biological Safety Research Scientist, you will apply your technical skills to design and develop our safety systems which detect harmful behaviours and to prevent misuse by sophisticated threat actors. You will be at the forefront of defining what responsible AI safety looks like in the biological domain, working across research, policy, and engineering to translate complex biosecurity concepts into concrete technical safeguards. This is a unique opportunity to shape how frontier AI models handle dual-use biological knowledge—balancing the tremendous potential of AI to accelerate legitimate life sciences research while preventing misuse by sophisticated threat actors.

In this role, you will:

• Design and execute capability evaluations ('evals') to assess the capabilities of new models
• Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimising for both robustness against adversarial attacks and low false-positive rates for legitimate researchers
• Analyse safety system performance in traffic, identifying gaps and proposing improvements
• Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces
• Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle
• Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety
• Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these

You may be a good fit if you have

• A PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, OR equivalent professional experience
• Extensive experience in scientific computing and data analysis, with proficiency in programming (Python preferred)
• Deep expertise in modern biology, including both 'reading' (e.g. high-throughput measurement, functional assays) and 'writing' (gene synthesis, genome editing, strain construction, protein engineering) techniques in biology
• Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks (e.g., Biological Weapons Convention, Australia Group guidelines)
• Strong analytical and writing skills, with the ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders
• Have a passion for learning new skills and an ability to rapidly adapt to changing techniques and technologies
• Comfort working in a fast-paced environment where priorities may shift as AI capabilities evolve

Preferred Qualifications

• Background in AI/ML systems, particularly experience with large language models
• Experience in developing ML for biological systems
• Extensive experience in complex projects with multiple stakeholders

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing

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