Computational Chemist

San Francisco, California
US$100000 - US$140000 per annum

SCIENTIST I/SCIENTIST II

$100,000-$140,000 + STOCK OPTIONS

SAN FRANCISCO BAY AREA

Are you looking for a dynamic opportunity in an innovative company to work on a breadth of therapeutic spaces? Are you looking to make an impact in oncology or immune oncology?

THE COMPANY

This therapeutics company is using small molecule drugs to bring novel therapies to a wide range of individuals. They are a public company that targets a broad range of diseases. The company prides themselves on their innovative technology, creating a high risk, high reward company environment. The company is looking for a self-starter, who is ready to make an impact in the space.

THE ROLE

As a scientist I or scientist II, you will be a crucial member to the function of the company.

In specific, you can expect to be involved in the following:

  • Collaborating with medicinal chemists
  • Developing new work flows and models
  • Support on research-oriented work flows

YOUR SKILLS AND EXPERIENCE

As a scientist I or scientist II, you will have the following skills and experience:

  • PhD in chemistry, biology, structural biology, computational biology, or related field
  • Extensive structure-based experience
  • Extensive experience in medicinal chemistry
  • Extensive small molecule experience
  • Experience in Schrodinger, Python or Moe

THE BENEFITS

$100,000-$140,000 + stock options

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San Francisco, California
US$100000 - US$140000 per annum
  1. Permanent
  2. Health Informatics

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Join a well-established start-up, as one of the first Machine Learning experts!

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Computer Vision in Healthcare Beyond Covid-19

2020. It sounds like the name of a futuristic science-fiction movie or TV show, doesn’t it? Maybe it is. And like our favorite sci-fi flicks there are cutting edge changes happening in real time. We’re the characters in this story and the Computer Vision and Artificial Intelligence partnerships in healthcare are moving fast to help us take care of ourselves. When computers can see what we can’t. When AI can help us make more informed decisions. When the two are combined to help doctors and providers work more efficiently to save lives, that’s when the cutting-edge shines. From the collaboration of Johns Hopkins, the CDC, and the WHO mapping out the data to contact traces to medical professionals on the front lines, we’ve been focused on one thing. Saving lives. But, what about the other medical issues that affect us? Heart disease. Cancer. Neurological illnesses.  What if the latest advances in healthcare could help here, too? Five Ways Computer Vision Helps Healthcare Providers Identifies leading causes of medical illnesses in a time-sensitive manner by creating algorithms for image processing, classification, segmentation, and object detection.Develops deep learning models to create neural networks.Collaboration of teams of scientists working together for the advancement of projects and present findings to business leaders, stakeholders, and clients.Allows providers to spend more time with their patients.Optimization of medical diagnoses using deep learning so doctors can spend more time with patients to help see and solve the problem faster. Computer Vision Engineer Meets AI Professional Artificial Intelligence (AI) offers real world answers in healthcare the world needs today. Computer Vision Engineers build the means to which AI helps providers, patients, and leaders make informed decisions. Core requirements for both roles include, but aren’t limited to: Experience in machine learning and deep learning.How to build computer vision algorithms and probability models.Problem-solving skills, creativity, ingenuity, and innovation.Languages like Python, R, Hadoop, Java, and Spark.Be able to see the big picture while at the same time finding the devil in the details. Always striving to improve, to make better, to advance the technology within the industry. The Challenges and the Potential of Technology in Healthcare At the moment, Computer Vision, AI, and other healthcare technology models are localized to individual placements. The next step is to have these technologies ‘speak’ to each other across hospitals, provider’s offices, telehealth applications, and electronic health records management for a more cohesive benefit of care. As this year rounds to a close, we know the vulnerabilities of our healthcare system, and can find solace in the though that technology is bringing it forward at lightning speed. Automation and telehealth appointments have made it a breeze to talk to our doctors and get results faster. We can pay our bills with the click of a button and even carve out a payment plan, if need be. All without leaving our homes. The data now available to us and our providers offers a foundation, a benchmark of information, so our doctors can make more informed decisions. This data goes beyond the individual, it helps set a precedent for not only individuals, but also entire populations, to help us identify future health issues, epidemics, and pandemics.  Stored data is private and stays within its construct of hospital or doctor’s office, but from it we can create models to plan for the future. Want to make your make your mark in the healthcare and tech industry? We may have just the role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

A Slam-Dunk Career as a SLAM Engineer

Philadelphia. It’s known for it’s Philly Cheesesteak, the Liberty Bell, and where the Constitution was signed. Always on the cutting edge, Philadelphia is a land of firsts. You may or not know this, but one of its firsts was to have the first general use computer in 1946. Is it any wonder then that a company there is building robots to navigate GPS denied environments and was begun by leaders in the Computer Vision space?  Beyond the Roomba If you consider the Roomba, the autonomous vacuum that sweeps up pet hair, dirt, and other unwanted product, how does it know where to go? How does it know to go under a table or chair or around a wall to the next room? How does it know to avoid the dog, cat, or you? On nearly the smallest scale, this little round machine is a personal version of simultaneous location and mapping (SLAM).  However, the computational geometry method of this mapping and localization technique extends in a wide variety of arcs. Here are a few to get you thinking: GPS Navigation SystemsSelf-driving carsUnmanned Aerial Vehicles (UAV)Autonomous Underwater Vehicles (AUV)DronesRobotsVirtual Reality (VR)Augmented Reality (AR)Monocular Camera...and more There’s even a version which is used in the Life Sciences called RatSLAM. But we’ll visit that in another article. The uses and benefits of this simultaneous location and mapping technique are exponential even with some of the challenges posed by Audio-Visual and Acoustic SLAM. What is SLAM? Essentially, it is the 21st century version of cartography or mapping. Except in this case, not only can it map the environment, but it can also locate your place in it. When you want to know where the nearest restaurant is, you simply type in ‘restaurant near me.’ And soon, a list appears on your phone with a list radiating from nearest location outward.  Imagine you’re lost on a hike, you manage to find signal, and soon your GPS is offering directions on which way to move toward civilization.  This is Simultaneous Localization and Mapping. It locates you, your vehicle, a robot, drone, unmanned aerial vehicle or self-driving car and puts people and things in the direction it thinks they want to go or should go to get to safety. While mapping is at the epicenter of SLAM Computer Vision Engineering, there are other elements within the field as well. But let’s begin with mapping. Topological maps offer a more precise representation of your environment and can therefore help ensure consistency on a global scale.  Just as humans do when giving directions, sensor models offer landmark-based approaches to make it easier to determine your location within the map’s structure and raw-data approaches which makes no assumptions. Landmarks such as wifi or radio beacons are some of the easiest to locate, but may not always be correct which is where the raw-data approach comes in to offer its two cents as a model of location function. Four Challenges of SLAM GPS sensors may not function properly in chaotic environments such as military conflict. }Non-static environments such as pedestrians or high traffic areas with multiple vehicles make locations difficult to pinpoint.In Acoustic SLAM, challenges include inactivity and environmental noise as well as echo. Sound localization requires a robot or machine to be equipped with a microphone in order to go in the requested direction. Five Additional Forms of SLAM Tactile (sensing by touch)RadarAcousticAudio-Visual (a function of Human-Robot interaction)Wifi (sensing strength of nearby access points) Ready to Explore a Robotics and Computer Vision Career? Whether you’re interested in a slam dunk career as a SLAM Engineer or looking for your first or next role in Big Data, Web Analytics, Advanced Analytics & Insight, Life Science Analytics, or Data Science, take a look at our current vacancies or get in touch one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.

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