Cytokinetics is dedicated to advancing the frontiers of technology through the strategic application of artificial intelligence, machine learning, image analysis, and computational biology and chemistry. We are at the forefront of innovation, driving impactful solutions in drug discovery. As we expand our team, we are seeking a highly skilled Senior AI Expert to contribute to our ambitious projects and initiatives.We are seeking a dynamic experienced AI Expert with a Ph.D in Machine Learning, Artificial Intelligence, Computer Science, or a related field, accompanied degree in Bioinformatics, Cheminformatics, or a relevant discipline. This role requires extensive experience in building supervised learning models, particularly in image analysis, with a focus on phenotypic screening, images of cells, and cell parts. It is also essential to have experience with regression models for predictors and a deep understanding of biological data analysis. Experience of ML utilization for classification, regression, and clustering of highly complex metabolomic and/or proteomics data is also desired.ResponsibilitiesCollaborate closely with the Director of Discovery Technologies to foster and grow AI implementation, infrastructure, and processes within the organization.Lead the research, development, and implementation of advanced machine learning and deep learning algorithms to solve complex problems within Biological Sciences. This includes supervised, non-supervised analysis & visualization, as well as image analysis, particularly in phenotypic screening, images of cells, and cell parts.Utilize regression models for predictors in biological data analysis to derive meaningful insights and predictions from large-scale datasets.Collaborate closely with interdisciplinary teams to define project objectives, design experimental frameworks, and deliver innovative solutions that drive impact across Research Discovery programs.Conduct thorough data preprocessing, feature extraction, and dimensionality reduction to optimize model performance and scalability.Stay abreast of the latest developments in AI, machine learning, bioinformatics, and cheminformatics, and integrate emerging technologies and methodologies into our workflows.Provide technical leadership and mentorship to colleagues, fostering a collaborative and intellectually stimulating environment.Evaluate and compare different machine learning frameworks and libraries to identify the most suitable tools for specific tasks.Contribute and assist to the development and documentation of best practices, standards, and guidelines for AI and machine learning within the organization.Communicate findings and results effectively to both technical and non-technical stakeholders through presentations, reports, and documentation.Take ownership of projects from conception to deployment, ensuring high-quality and reliable solutions are delivered on time and within budget constraints.Report regularly to the Director of Discovery Technologies on project progress, challenges, and opportunities for improvement, providing strategic insights and recommendations for further advancements.QualificationsPh.D. in Machine Learning, Artificial Intelligence, Computer Science, Bioinformatics, or relevant disciplineMinimum 3-7 years of experience that may include post-doc in machine learning and AI field utilizing large-scale datasets and cutting-edge machine learning techniques to develop accurate and robust supervised learning modelsProven expertise in building supervised learning models, with a focus on image analysis and biological data analysis, including proteomics and/or metabolomics.Strong background in statistical analysis, data visualization, and algorithm development, with a demonstrated ability to tackle complex problems in interdisciplinary domains.Proficiency in programming languages such as Python, Matlab, R, and experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).Excellent communication skills, with the ability to convey technical concepts effectively to diverse audiences, both verbally, written, and presentation style.Proactive and results-driven approachPassion for continuous learning and innovationNice-to-Haves:Experience with cloud-based machine learning platforms such as Amazon SageMaker or Apache Spark-based solutions like Databricks is advantageous.Familiarity with other Amazon Cloud AWS servicesExperience with DeepCut for processing image analysis of pre-clinical studiesExperience with Cellpose for processing phenotypic cell images#J-18808-Ljbffrby Jobble

The Opportunity State-of-the-art technologies that measure multiple cellular aspects are at the heart of Insitro's efforts to accelerate drug development. We routinely generate in-house large scale omics datasets to derive clinically relevant insights, as well as leverage publicly available resources. We are looking to hire a new team member with expertise in developing ML methods for omics readouts, in domains such as single cell transcriptomics (e.g. batch correction, trajectory analysis, foundation models), spatial omics (e.g. cell to cell communication, spatial deconvolution), or multi-omics (e.g. integration of distinct readouts). Your expertise will help the team navigate the complexities of transcriptomics data.It will also ensure that the tools being developed are accurate and effective and that the analyses are performed to the highest rigor and in line with best practices in the field. In this role, you will directly impact all target prioritization efforts, advance our understanding of diseases, and aid the development of new treatments. Towards these goals, you will build cutting-edge ML methods that address unmet company needs for in-house generated datasets (with an emphasis on multimodal measurements and data integration) as well as for human cohort data in order to extract insights about disease mechanisms. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists that strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. You will be joining a vibrant biotech startup that has long-term stability, due to significant funding, and is in a high growth phase, and you will have many opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients! About You <ul><li>Ph.D. in computer science, machine learning, computational biology, systems biology, or a related discipline.</li><li>Extensive hands on experience developing ML methods for omics data, especially single-cell RNA-seq data</li><li>Hands on experience analyzing single-cell RNA-seq data, in particular familiarity with the scverse ecosystem.</li><li>Experience with spatial transcriptomics and/or proteomics</li><li>Some understanding of human physiology or disease biology (e.g. neurosciences, cancer biology).</li><li>Familiarity with data from CRISPR-based experiments (e.g. perturb-seq)</li><li>Strong programming skills in scientific programming languages (i.e., Python)</li><li>Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review)</li><li>Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions</li><li>Publication record of meaningful contributions to high-quality work in relevant computational biology, systems biology, life sciences, or biomedical venues</li><li>Passion for making a difference in the world</li></ul> Nice to Have <ul><li>Experience working with diverse functional genomic assay data (RNA/ATAC/ChIP-seq, etc)</li><li>Hands on experience working with microscopy data or similar biomedical or biophysical imaging modalities</li><li>Understanding of systems biology approaches, including network analysis</li><li>First-hand experience studying diseases using omics or imaging data</li><li>Experience with proteomics and/or metabolomics data generated through mass spectrometry</li><li>Passionate about troubleshooting, asking questions and learning independently</li><li>Experience with modeling time-series datasets</li><li>Familiarity with cloud computing services (e.g., AWS or azure)</li><li>Demonstrated ability to write software in a team, industry experience or substantial involvement with open source projects.</li><li>Experience building infrastructure for data processing</li></ul> Compensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $185,000 - $270,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: <ul><li>401(k) plan with employer matching for contributions</li><li>Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees on our base plans), as well as mental health and well-being support</li><li>Open, flexible vacation policy</li><li>Paid parental leave</li><li>Quarterly budget for books and online courses for self-development</li><li>Support to occasionally attend professional conferences that are meaningful to your career growth and development</li><li>New hire stipend for home office setup</li><li>Monthly cell phone & internet stipend</li><li>Access to free onsite baristas and cafe with daily lunch and breakfast</li><li>Access to free onsite fitness center</li><li>Commuter benefits</li></ul> #LI-Hybrid About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience, oncology and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.

Machine Learning Scientist Jobs in South San Francisco, CA

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Machine Learning Scientist Jobs in South San Francisco, CA

Senior Machine Learning ScientistApril 24, 2024

Senior Machine Learning ScientistApril 21, 2024

Senior Machine Learning ScientistApril 19, 2024

Machine Learning Scientist OmicsApril 16, 2024

Machine Learning Scientist OmicsApril 13, 2024

Machine Learning Scientist OmicsApril 11, 2024

Machine Learning Scientist OmicsApril 10, 2024