No, to produce milk a cow needs to be pregnant or recently pregnant so milk production requires forced insemination and giving birth to the calf. After birth, the calf is separated from the mother to be caged for veal, raised as a milking cow, etc., and the mother is re-inseminated so she can keep producing milk and the process starts over.
The process you describe is true for organic milk, but less true for regular milk. Modern dairy farms use sex selected semen to prevent males from being born and they use synthetic hormones to extend milk production. Not much excess calving happens in big dairy.
I work in a quantitative science in academia, and this is a major reason stopping me from making the switch. It can be incredibly time consuming to solve problems. In my college days I spent days trying to get my keyboard backlight to work and my trackpad to work properly. I have a bunch of research work that needs to get done yesterday and I simply don't have time to troll forums or hang out in IRC for someone who might help me. Throw in some daily driver software that I am comfortable using does not run on Linux and I am still stuck on a Mac many years later.
This question comes up over and over again in r/bioinformatics, so I put together a short guide that I hope will be helpful for those considering getting into the field.
Cold Spring Harbor Laboratory | Postdoctoral Fellow | Cold Spring Harbor, NY (outside of NYC) | Onsite | Full Time
Two computational postdoctoral positions are available immediately at Cold Spring Harbor Laboratory (CSHL) in the lab of Saket Navlakha ( navlakhalab.net/ ).
Position details
* Work at the interface of theoretical computer science, machine learning, and systems biology.
* Develop bleeding edge machine learning algorithms to answer fundamental questions about biology and disease.
* Discover new ideas for computation by studying problem-solving strategies used in nature (“algorithms in nature”).
* Recent lab successes have been in neural circuit computation and plant architecture optimization, but suggestions for new areas of interest (e.g. cancer) are also welcome.
* Ample opportunities to publish in high tier journals (PI has recent publications in Science and PNAS).
Required Qualifications
* PhD (or graduating soon) in computer science or related computational/bioinformatics field.
* Strong algorithmic and programming skills.
* First author publications in computational biology conferences or journals.
Preferred Qualifications
* Strong publication track record. A first author publication in a high impact factor (>4-5) journal or a paper presented at a top conference (e.g. RECOMB, ISMB, WABI, PSB, BIBM, NIPS, ICML, KDD, PAKDD, ICLR, AISTATS, UAI, ICDE, ICDM, SDM, or CIKM).
* Computer science PhD.
* Machine learning experience.
* Experience or interest in learning biology and collaborating with experimentalists.
Interested? Please submit a CV and a short description of how your research interests overlap with the PI's to paul@talentseq.com .
Not just at the Kindle store. The eBook is also on sale at Apple Books, Barnes & Noble, BAM!, Google Play, and Kobo. They are all $3.99, same as the Kindle sale price.
I read this shortly after the Internet History Podcast episode with the authors. It is a good, detailed but bite-sized book. Very inspiring and very well written.
