Ancestry’s Post

Happy Easter, Everyone!🌷🐣🐰   At this time of the year, it's always good to assess if you are aligned with your 2024 goals. Whether you're aiming for personal growth, professional achievements, or simply seeking new adventures, let this season be a reminder to realign your path with your aspirations. If your career was something you wanted to focus on, I currently have some interesting opportunities that could be of interest! 🚀 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗮𝗹 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿  𝗕𝗮𝘀𝗲𝗱: 𝗣𝗮𝗿𝗶𝘀  🍳 Master's or Ph.D. degree in Computer Science, Bioinformatics, Computational Biology, or a related field. 🍳 Strong background in machine learning, with 5+ years of hands-on experience in developing and deploying machine learning models for real-world applications. 🍳 Experience in Deep Learning is required, particularly with intricate and expansive datasets such as biomedical imaging, graph-structured data, and physics simulations, ideally in a production setting.   𝗖𝗵𝗲𝗺𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁  𝗕𝗮𝘀𝗲𝗱: 𝗣𝗮𝗿𝗶𝘀  🐣 Ph.D. or equivalent experience in Computer Science, Machine Learning, Physics or Computational Chemistry, Computational Biology with ML applications. 🐣 Proven expertise in applying machine learning techniques to drug discovery, with a focus on molecular modeling and cheminformatics. 🐣 Proficient in programming languages commonly used in data science and machine learning (e.g., Python, TensorFlow, PyTorch).   𝗦𝗲𝗻𝗶𝗼𝗿 𝗕𝗶𝗼𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝗶𝗮𝗻  𝗕𝗮𝘀𝗲𝗱: 𝗣𝗮𝗿𝗶𝘀  💐 PhD in Bioinformatics, Computational Biology, Genetics, or a related field. 💐 Proficiency in programming languages commonly used in bioinformatics such as Python and R. 💐 Strong understanding of molecular biology, genetics, and genomics principles, with demonstrated wet lab or biology experience.   𝗕𝗶𝗼𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝗶𝗮𝗻  𝗕𝗮𝘀𝗲𝗱: 𝗕𝗲𝗿𝗹𝗶𝗻. 𝗚𝗲𝗿𝗺𝗮𝗻𝘆  🍫 Master's or Ph.D. degree in computer science, bioinformatics, or a related field. 🍫 Demonstrated expertise in applying machine learning algorithms to genomics data analysis. 🍫 Proficiency in programming languages commonly used in machine learning and bioinformatics, such as Python, R, and/or Julia.   𝗦𝗲𝗻𝗶𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿  𝗕𝗮𝘀𝗲𝗱: 𝗢𝘀𝗹𝗼, 𝗡𝗼𝗿𝘄𝗮𝘆 𝗼𝗿 𝗛𝗲𝗶𝗱𝗲𝗹𝗯𝗲𝗿𝗴, 𝗚𝗲𝗿𝗺𝗮𝗻𝘆  🐤 Master's or Ph.D. degree in computer science, bioinformatics, or a related field. 🐤 Demonstrated expertise in applying machine learning algorithms to genomics data analysis. 🐤 Proficiency in programming languages commonly used in machine learning and bioinformatics, such as Python, R, and/or Julia.   Whether it's exploring new roles, honing your skills, or diving into exciting projects, reach out now to book in a call to speak further!! #HappyEaster #jobopportunities #hiring #bioinformatician #machinelearning #deeplearning #genomics #software🌼

We have multiple open positions at Recursion. Position descriptions below and the links in the comments. -Staff #machinelearning Scientist The main focus in this role is building multimodal biological foundation models to decode biology and radically improve lives. Hiring Manager: Oren Kraus -Senior Data Scientist Hiring Manager: Ben Fogelson - Principal Computational Biologist Hiring Manager: Michael Cuccarese You’ll join Inception Labs, a research and development team within Recursion that is a cross-functional group of exceptional biologists, engineers, product managers, machine learning scientists, computational biologists, and data scientists. If you are interested in using your #datascience, #machinelearning and computational biology expertise to tackle hashtag #drugdiscovery problems, check the roles, and apply for the ones that best suit your expertise and interests. Recursion is a clinical stage TechBio company leading the space by decoding biology to industrialize drug discovery. Read more about us in our LinkedIn page and website. Feel free to share these positions with your network. #ComputationalBiology #datascience #deeplearning

We have multiple open positions at Recursion. Position descriptions below and the links in the comments. -Staff #machinelearning Scientist The main focus in this role is building multimodal biological foundation models to decode biology and radically improve lives. Hiring Manager: Oren Kraus -Senior Data Scientist Hiring Manager: Ben Fogelson - Principal Computational Biologist Hiring Manager: Michael Cuccarese You’ll join Inception Labs, a research and development team within Recursion that is a cross-functional group of exceptional biologists, engineers, product managers, machine learning scientists, computational biologists, and data scientists. If you are interested in using your #datascience, #machinelearning and computational biology expertise to tackle #drugdiscovery problems, check the roles, and apply for the ones that best suit your expertise and interests. Recursion is a clinical stage TechBio company leading the space by decoding biology to industrialize drug discovery. Read more about us in our LinkedIn page and website. Feel free to share these positions with your network. #ComputationalBiology #datascience #deeplearning

𝗪𝗵𝗮𝘁 𝘄𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱... 𝗳𝗿𝗼𝗺 𝗿𝗲𝗰𝗿𝘂𝗶𝘁𝗶𝗻𝗴 𝗮 𝗱𝗿𝘂𝗴 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 𝗶𝗻 𝟮 𝘄𝗲𝗲𝗸𝘀 Data Scientists are enabling the future of AI and ML powered drug discovery and design, utilising their computational biology and data analysis domain expertise. It's no surprise their skills are in high demand in the world of biotech and drug discovery. Here are three things we learned from helping a VP Data Science at a Bay Area AI-drug discovery biotech recruit a Sr Data Scientist in 2 weeks: 💊𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗼𝗻 𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: despite the HQ been in the Bay, the VP Data Science was pro-remote working, meaning our talent pool increased tenfold, and we were able to conduct streamlined virtual interviews in week 1, and an offer accepted in week 2. It's no surprise their existing team had an impressive 𝘳𝘦𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘳𝘢𝘵𝘦 𝘰𝘧 >95%. 💊𝗕𝗶𝗼𝗺𝗮𝗿𝗸𝗲𝗿 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: with the surge of biomarker discovery research, it was reassuring to see lots of recent data scientists majoring in deep machine learning with biomarker ID or single cell transcriptomic approaches. 💊𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗺𝗲𝗲𝘁𝘀 𝘀𝘆𝗻𝗲𝗿𝗴𝗶𝘀𝘁𝗶𝗰 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝗽𝗵𝗮𝗿𝗺𝗮𝗰𝗼𝗹𝗼𝗴𝘆: a lot of prospects were showing a keen interest in the emerging field of multi-drug target research which utilizes deep learning computational algorithms to overcome the analysis of very big biological data sets. Although this particular client had no existing pipeline applications here, it signalled pro-activity and awareness to emerging trends in the field, which the hiring team loved. AI and ML technology will continue to be hot topics across the biotech field for years to come, and the demand for talent isn't slowing down. Get in touch if you're seeking guidance on how to identify and hire the right data scientists for your drug discovery/pipeline goals: E: Adam.butler@mason-harding.com #datascience #machinelearning #drugdiscovery #masonharding

Which is better! Bioinformatics or Data Science Two prominent career paths that leverage data analysis are bioinformatics and data science. Choosing between these fields can be a challenging decision, as both offer unique opportunities and challenges. Let's explore the key considerations to help you make an informed choice. 1. Nature of the Data: - Bioinformatics: Specializes in biological data, dealing with genomics, proteomics, and other molecular data. Ideal for those passionate about unraveling the complexities of living organisms. - Data Science: Encompasses a broader spectrum, working with diverse datasets from various industries such as finance, healthcare, and e-commerce. 2. Educational Background: - Bioinformatics: Often requires a background in biology, genetics, or a related field, in addition to proficiency in computational methods. - Data Science: Welcomes diverse educational backgrounds, including computer science, statistics, engineering, or even a strong foundation in a particular domain like finance or healthcare. 3. Job Opportunities: - Bioinformatics: Opportunities in research institutions, pharmaceutical companies, and healthcare organizations, agricultural research, biomedical engineering, environmental engineering and remediation and lots more. - Data Science: Versatile career options across various industries, including finance, marketing, healthcare, and technology, dealing with predictive modeling, machine learning, and business intelligence. 4. Skill Set: - Bioinformatics: Requires a deep understanding of biological systems, proficiency in programming languages like Python or R, and expertise in specialized bioinformatics tools. - Data Science: Demands a strong foundation in programming languages, statistical analysis, machine learning, and data visualization, often using tools like Python, R, and frameworks like TensorFlow or PyTorch. 5. Impact and Purpose: - Bioinformatics: Offers the opportunity to contribute directly to advancements in medicine, genetics, and personalized Healthcare, and many other areas making a tangible impact on human, plant and animal health. - Data Science: Also provides a broad impact, allowing individuals to address challenges in diverse fields, ranging from optimizing business strategies to developing solutions for societal issues. Conclusion: If you are fascinated by the intricacies of biological systems and eager to contribute to advancements in healthcare (one of the numerous aspects of bioinformatics), bioinformatics may be your calling. On the other hand, if you are drawn to the versatility of data-driven solutions across industries, data science offers a broader canvas for exploration. We at NOBLEKINMAT Ltd offer comprehensive Bioinformatics Courses that fit into your need and for you to thrive in the industry. Reach out to us through Noblekinmat@gmail.com or visit our website www.noblekinmat.com for more. #Bioinformatics #africa

Bioinformatics vs Data science

Which is better! Bioinformatics or Data Science Two prominent career paths that leverage data analysis are bioinformatics and data science. Choosing between these fields can be a challenging decision, as both offer unique opportunities and challenges. Let's explore the key considerations to help you make an informed choice. 1. Nature of the Data: - Bioinformatics: Specializes in biological data, dealing with genomics, proteomics, and other molecular data. Ideal for those passionate about unraveling the complexities of living organisms. - Data Science: Encompasses a broader spectrum, working with diverse datasets from various industries such as finance, healthcare, and e-commerce. 2. Educational Background: - Bioinformatics: Often requires a background in biology, genetics, or a related field, in addition to proficiency in computational methods. - Data Science: Welcomes diverse educational backgrounds, including computer science, statistics, engineering, or even a strong foundation in a particular domain like finance or healthcare. 3. Job Opportunities: - Bioinformatics: Opportunities in research institutions, pharmaceutical companies, and healthcare organizations, agricultural research, biomedical engineering, environmental engineering and remediation and lots more. - Data Science: Versatile career options across various industries, including finance, marketing, healthcare, and technology, dealing with predictive modeling, machine learning, and business intelligence. 4. Skill Set: - Bioinformatics: Requires a deep understanding of biological systems, proficiency in programming languages like Python or R, and expertise in specialized bioinformatics tools. - Data Science: Demands a strong foundation in programming languages, statistical analysis, machine learning, and data visualization, often using tools like Python, R, and frameworks like TensorFlow or PyTorch. 5. Impact and Purpose: - Bioinformatics: Offers the opportunity to contribute directly to advancements in medicine, genetics, and personalized Healthcare, and many other areas making a tangible impact on human, plant and animal health. - Data Science: Also provides a broad impact, allowing individuals to address challenges in diverse fields, ranging from optimizing business strategies to developing solutions for societal issues. Conclusion: If you are fascinated by the intricacies of biological systems and eager to contribute to advancements in healthcare (one of the numerous aspects of bioinformatics), bioinformatics may be your calling. On the other hand, if you are drawn to the versatility of data-driven solutions across industries, data science offers a broader canvas for exploration. We at NOBLEKINMAT Ltd offer comprehensive Bioinformatics Courses that fit into your need and for you to thrive in the industry. Reach out to us through Noblekinmat@gmail.com or visit our website www.noblekinmat.com for more. #Bioinformatics #africa

Job Description - Job Title - Data Scientist (Genomics) 100 % Remote  Must have genomics. Ph.D. or a master's degree with professional experience. Candidate must have 3+ years of experience with Python Proficiency with TensorFlow and PySpark Proficiency with unit testing Proficiency with machine learning, specifically working with transformers Experience with Docker and Kubernetes  Email:farha.khan@tekinspirations.com #Genomics #Docker #Kubernetes #Pyspark #TensorFlow #Python

For those eager to dive deeper into this field, check this out!📌👌

Which is better! Bioinformatics or Data Science Two prominent career paths that leverage data analysis are bioinformatics and data science. Choosing between these fields can be a challenging decision, as both offer unique opportunities and challenges. Let's explore the key considerations to help you make an informed choice. 1. Nature of the Data: - Bioinformatics: Specializes in biological data, dealing with genomics, proteomics, and other molecular data. Ideal for those passionate about unraveling the complexities of living organisms. - Data Science: Encompasses a broader spectrum, working with diverse datasets from various industries such as finance, healthcare, and e-commerce. 2. Educational Background: - Bioinformatics: Often requires a background in biology, genetics, or a related field, in addition to proficiency in computational methods. - Data Science: Welcomes diverse educational backgrounds, including computer science, statistics, engineering, or even a strong foundation in a particular domain like finance or healthcare. 3. Job Opportunities: - Bioinformatics: Opportunities in research institutions, pharmaceutical companies, and healthcare organizations, agricultural research, biomedical engineering, environmental engineering and remediation and lots more. - Data Science: Versatile career options across various industries, including finance, marketing, healthcare, and technology, dealing with predictive modeling, machine learning, and business intelligence. 4. Skill Set: - Bioinformatics: Requires a deep understanding of biological systems, proficiency in programming languages like Python or R, and expertise in specialized bioinformatics tools. - Data Science: Demands a strong foundation in programming languages, statistical analysis, machine learning, and data visualization, often using tools like Python, R, and frameworks like TensorFlow or PyTorch. 5. Impact and Purpose: - Bioinformatics: Offers the opportunity to contribute directly to advancements in medicine, genetics, and personalized Healthcare, and many other areas making a tangible impact on human, plant and animal health. - Data Science: Also provides a broad impact, allowing individuals to address challenges in diverse fields, ranging from optimizing business strategies to developing solutions for societal issues. Conclusion: If you are fascinated by the intricacies of biological systems and eager to contribute to advancements in healthcare (one of the numerous aspects of bioinformatics), bioinformatics may be your calling. On the other hand, if you are drawn to the versatility of data-driven solutions across industries, data science offers a broader canvas for exploration. We at NOBLEKINMAT Ltd offer comprehensive Bioinformatics Courses that fit into your need and for you to thrive in the industry. Reach out to us through Noblekinmat@gmail.com or visit our website www.noblekinmat.com for more. #Bioinformatics #africa