Job Description
Scispot
Computational Biologist (AI/ML + Bio background)
Scispot • India • via LinkedIn
CA$40K–CA$60K a year
Internship
Apply on LinkedIn
Job description
About Scispot
Scispot is a trailblazing company developing the world's best and first data infrastructure for lifescience companies. We work at the intersection of biotech, AI, and ML to enable innovation and advancement in the life sciences industry.
Job Description
• We are seeking a Computational Biologist with extensive experience in AI and Machine Learning, and a background in biotech. The successful candidate will work with our data scientists and bioinformatics teams to design and implement ETL pipelines and computational frameworks, integrate and analyze genomic and transcriptomic datasets, and assist in the interpretation of gene expression data.
Key Responsibilities
• Run biotech R&D pipelines as a data scientist or data engineer
• Build ETL / ELT pipelines
• Work with open-source Apache products such as Airflow, Nifi
• Establish computational frameworks for integrating, accessing, and analyzing genomic and transcriptomic datasets
• Develop analysis workflows for high-throughput DNA, and RNA sequencing data
• Integrate new pipelines with other components of Scispot’s tech stack
• Assist in the analysis and interpretation of gene expression data
• Work with scientists to leverage Bioinformatics datasets and assist in efforts of target assessment
• Collaborate with wet-lab scientists, data scientists, and bioinformaticians to design experiments, analyze data, and interpret the results
• Recommend cleansing and transformation rules required to make the datasets ready for AI/ML
• Experience in data governance modeling
• Experience working with HTS Omics sequencing data (Eg: RNAseq, scRNAseq, ISLAND, WES)
Required Qualifications And Experience
• Currently pursuing PhD or MSc in Bioinformatics, Computational Biology, or a related field
• Demonstrated expertise in R, Python, and building complex code in a collaborative environment
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience working with high-throughput sequencing data (RNAseq, scRNAseq, WES)
• Proficiency in biological database management and the use of bioinformatics tools and software
• Extensive knowledge in applying machine learning and statistical modeling to biological datasets
• Proficiency in processing and analyzing high dimensional biological data
• Familiarity with public biological data sources and repositories
• Experience with biological data standards, ontologies, and metadata
• Familiarity with cloud-based data storage and analysis solutions is preferred
• Strong analytical skills related to working with large diverse datasets
• A demonstrated ability to find creative and functional solutions to complicated problems
• Excellent documentation skills with impeccable attention to detail
• Exceptional communication skills and the ability to express complex ideas in understandable ways
• Strong critical thinking skills and the ability to handle ambiguity in data analysis
• Proven track record of publishing relevant work in high-impact journals is preferred
• If you are passionate about contributing to groundbreaking work in the life sciences and enjoy working in a fast-paced, innovative environment, we would love to hear from you.
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See web results for Scispot
Applix
Senior Mechanical Research Engineer
Applix • via Instahyre
Full–time
Apply on Instahyre
Job description
We are looking for a Senior Mechanical Engineering Research and Design Engineer to play a crucial role in developing and enhancing the Applix AI Copilot. The ideal candidate will bring a unique blend of mechanical engineering expertise, systems thinking, and enthusiasm for AI-driven design optimization. You will work closely with our interdisciplinary team to research, implement, and refine cutting-edge design optimization techniques and models.
Responsibilities:
• Contribute to the development and improvement of AI-driven design optimization algorithms for mechanical systems.
• Apply and enhance Design for X (DFx) principles within the Applix AI Copilot platform, focusing on manufacturability, assembly, quality, performance, and cost.
• Implement and refine Failure Mode and Effects Analysis (FMEA) methodologies in our AI-driven quality control processes.
• Research and integrate state-of-the-art mechanical design optimization techniques into our platform.
• Collaborate with cross-functional teams (AI engineers, software developers, UX designers) to enhance the Applix AI Copilot's capabilities and user experience.
• Analyze complex manufacturing data to identify patterns and opportunities for optimization.
• Develop and maintain documentation for design optimization models and processes.
• Contribute to the continuous learning and improvement of our AI system by providing domain expertise and feedback.
• Identify and analyze defects at both production and post-production stages, conducting comprehensive Root Cause Analysis (RCA).
• Examine and interpret diverse data points from various sources, including production inspections, warranty recall data, user complaints, telemetry data, and information from IoT devices, CRM, ERP, and MES systems.
• Develop and implement predictive analytics models to identify potential defects before they occur.
• Create prescriptive models that recommend actions to prevent predicted defects.
• Continuously refine and improve defect prediction and prevention models based on new data and insights.
Requirements:
• Master's or Ph. D. in Mechanical Engineering or a related field.
• 5+ years of experience in mechanical design, with a focus on design optimization and manufacturing processes.
• Strong understanding of DFx principles, including Design for Manufacturing (DFM) and Design for Assembly (DFA).
• Expertise in FMEA and other quality control methodologies in manufacturing.
• Experience with CAD/CAM/CAE software and simulation tools.
• Proven experience in defect analysis and root cause identification in manufacturing environments.
• Strong background in data analysis and interpretation, particularly with diverse data sources relevant to manufacturing and product lifecycle.
• Experience with predictive and prescriptive analytics, preferably in a manufacturing or engineering context.
• Familiarity with machine learning and AI concepts, particularly as applied to engineering design.
• Strong analytical and problem-solving skills, with the ability to think critically about complex systems.
• Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Preferred:
• Experience with programming languages such as C++, Python, and MATLAB for data analysis and model development.
• Knowledge of Industry 4.0 concepts and technologies.
• Familiarity with cloud computing platforms and big data technologies.
• Experience with additive manufacturing technologies and processes.
• Track record of publications or patents in the field of design optimization or AI-driven manufacturing.
• Familiarity with IoT technologies and their application in manufacturing.
• Experience working with CRM, ERP, and MES systems, and ability to integrate data from these sources for comprehensive analysis.
• Knowledge of statistical process control (SPC) and its application in defect prevention.
• Experience with data visualization tools to effectively communicate complex data insights.
• Passionate about the intersection of AI and mechanical engineering.
• Enthusiastic team player with the ability to work in a fast-paced, innovative environment.
• Self-motivated learner, always eager to explore new technologies and methodologies.
• Creative problem-solver, able to think outside the box to address complex engineering challenges.
• Adaptable and resilient, comfortable with the uncertainties of cutting-edge technology development.
• Detail-oriented with a strong ability to see both the big picture and granular details in complex systems and data sets.
Computational Biologist (AI/ML + Bio background)
Scispot • India • via LinkedIn
CA$40K–CA$60K a year
Internship
Apply on LinkedIn
Job description
About Scispot
Scispot is a trailblazing company developing the world's best and first data infrastructure for lifescience companies. We work at the intersection of biotech, AI, and ML to enable innovation and advancement in the life sciences industry.
Job Description
• We are seeking a Computational Biologist with extensive experience in AI and Machine Learning, and a background in biotech. The successful candidate will work with our data scientists and bioinformatics teams to design and implement ETL pipelines and computational frameworks, integrate and analyze genomic and transcriptomic datasets, and assist in the interpretation of gene expression data.
Key Responsibilities
• Run biotech R&D pipelines as a data scientist or data engineer
• Build ETL / ELT pipelines
• Work with open-source Apache products such as Airflow, Nifi
• Establish computational frameworks for integrating, accessing, and analyzing genomic and transcriptomic datasets
• Develop analysis workflows for high-throughput DNA, and RNA sequencing data
• Integrate new pipelines with other components of Scispot’s tech stack
• Assist in the analysis and interpretation of gene expression data
• Work with scientists to leverage Bioinformatics datasets and assist in efforts of target assessment
• Collaborate with wet-lab scientists, data scientists, and bioinformaticians to design experiments, analyze data, and interpret the results
• Recommend cleansing and transformation rules required to make the datasets ready for AI/ML
• Experience in data governance modeling
• Experience working with HTS Omics sequencing data (Eg: RNAseq, scRNAseq, ISLAND, WES)
Required Qualifications And Experience
• Currently pursuing PhD or MSc in Bioinformatics, Computational Biology, or a related field
• Demonstrated expertise in R, Python, and building complex code in a collaborative environment
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience working with high-throughput sequencing data (RNAseq, scRNAseq, WES)
• Proficiency in biological database management and the use of bioinformatics tools and software
• Extensive knowledge in applying machine learning and statistical modeling to biological datasets
• Proficiency in processing and analyzing high dimensional biological data
• Familiarity with public biological data sources and repositories
• Experience with biological data standards, ontologies, and metadata
• Familiarity with cloud-based data storage and analysis solutions is preferred
• Strong analytical skills related to working with large diverse datasets
• A demonstrated ability to find creative and functional solutions to complicated problems
• Excellent documentation skills with impeccable attention to detail
• Exceptional communication skills and the ability to express complex ideas in understandable ways
• Strong critical thinking skills and the ability to handle ambiguity in data analysis
• Proven track record of publishing relevant work in high-impact journals is preferred
• If you are passionate about contributing to groundbreaking work in the life sciences and enjoy working in a fast-paced, innovative environment, we would love to hear from you.
Report this listing
More jobs at Scispot
See web results for Scispot
Applix
Senior Mechanical Research Engineer
Applix • via Instahyre
Full–time
Apply on Instahyre
Job description
We are looking for a Senior Mechanical Engineering Research and Design Engineer to play a crucial role in developing and enhancing the Applix AI Copilot. The ideal candidate will bring a unique blend of mechanical engineering expertise, systems thinking, and enthusiasm for AI-driven design optimization. You will work closely with our interdisciplinary team to research, implement, and refine cutting-edge design optimization techniques and models.
Responsibilities:
• Contribute to the development and improvement of AI-driven design optimization algorithms for mechanical systems.
• Apply and enhance Design for X (DFx) principles within the Applix AI Copilot platform, focusing on manufacturability, assembly, quality, performance, and cost.
• Implement and refine Failure Mode and Effects Analysis (FMEA) methodologies in our AI-driven quality control processes.
• Research and integrate state-of-the-art mechanical design optimization techniques into our platform.
• Collaborate with cross-functional teams (AI engineers, software developers, UX designers) to enhance the Applix AI Copilot's capabilities and user experience.
• Analyze complex manufacturing data to identify patterns and opportunities for optimization.
• Develop and maintain documentation for design optimization models and processes.
• Contribute to the continuous learning and improvement of our AI system by providing domain expertise and feedback.
• Identify and analyze defects at both production and post-production stages, conducting comprehensive Root Cause Analysis (RCA).
• Examine and interpret diverse data points from various sources, including production inspections, warranty recall data, user complaints, telemetry data, and information from IoT devices, CRM, ERP, and MES systems.
• Develop and implement predictive analytics models to identify potential defects before they occur.
• Create prescriptive models that recommend actions to prevent predicted defects.
• Continuously refine and improve defect prediction and prevention models based on new data and insights.
Requirements:
• Master's or Ph. D. in Mechanical Engineering or a related field.
• 5+ years of experience in mechanical design, with a focus on design optimization and manufacturing processes.
• Strong understanding of DFx principles, including Design for Manufacturing (DFM) and Design for Assembly (DFA).
• Expertise in FMEA and other quality control methodologies in manufacturing.
• Experience with CAD/CAM/CAE software and simulation tools.
• Proven experience in defect analysis and root cause identification in manufacturing environments.
• Strong background in data analysis and interpretation, particularly with diverse data sources relevant to manufacturing and product lifecycle.
• Experience with predictive and prescriptive analytics, preferably in a manufacturing or engineering context.
• Familiarity with machine learning and AI concepts, particularly as applied to engineering design.
• Strong analytical and problem-solving skills, with the ability to think critically about complex systems.
• Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Preferred:
• Experience with programming languages such as C++, Python, and MATLAB for data analysis and model development.
• Knowledge of Industry 4.0 concepts and technologies.
• Familiarity with cloud computing platforms and big data technologies.
• Experience with additive manufacturing technologies and processes.
• Track record of publications or patents in the field of design optimization or AI-driven manufacturing.
• Familiarity with IoT technologies and their application in manufacturing.
• Experience working with CRM, ERP, and MES systems, and ability to integrate data from these sources for comprehensive analysis.
• Knowledge of statistical process control (SPC) and its application in defect prevention.
• Experience with data visualization tools to effectively communicate complex data insights.
• Passionate about the intersection of AI and mechanical engineering.
• Enthusiastic team player with the ability to work in a fast-paced, innovative environment.
• Self-motivated learner, always eager to explore new technologies and methodologies.
• Creative problem-solver, able to think outside the box to address complex engineering challenges.
• Adaptable and resilient, comfortable with the uncertainties of cutting-edge technology development.
• Detail-oriented with a strong ability to see both the big picture and granular details in complex systems and data sets.
💡 Quick Summary
Seeking a career-building opportunity? The Senior Mechanical Research Engineer position is now open for candidates interested in the Work from home Jobs sector. This role in Jaipur offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Work from home Jobs is a plus.
